From fc3fc70aed6c25b07edcc413bb0a34ca1d5e0739 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:29:03 +0700
Subject: [PATCH 001/408] Add model
 2023-11-15-bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en

---
 ...few_shot_k_16_finetuned_squad_seed_2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..8b0e30d7014b99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-few-shot-k-16-finetuned-squad-seed-2` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en_5.2.0_3.0_1700058534351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2_en_5.2.0_3.0_1700058534351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.uncased_seed_2_base_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_uncased_few_shot_k_16_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/bert-base-uncased-few-shot-k-16-finetuned-squad-seed-2
\ No newline at end of file

From 0935cce4778a14df1eb5d5cf6011b3faabca88a8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:30:50 +0700
Subject: [PATCH 002/408] Add model
 2023-11-15-bert_qa_base_parsbert_uncased_finetuned_squad_fa

---
 ...ase_parsbert_uncased_finetuned_squad_fa.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_parsbert_uncased_finetuned_squad_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_parsbert_uncased_finetuned_squad_fa.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_parsbert_uncased_finetuned_squad_fa.md
new file mode 100644
index 00000000000000..c50eca4601652d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_parsbert_uncased_finetuned_squad_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian BertForQuestionAnswering Base Uncased model (from mhmsadegh)
+author: John Snow Labs
+name: bert_qa_base_parsbert_uncased_finetuned_squad
+date: 2023-11-15
+tags: [fa, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-parsbert-uncased-finetuned-squad` is a Persian model originally trained by `mhmsadegh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_parsbert_uncased_finetuned_squad_fa_5.2.0_3.0_1700058633009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_parsbert_uncased_finetuned_squad_fa_5.2.0_3.0_1700058633009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_parsbert_uncased_finetuned_squad","fa") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["اسم من چیست؟", "نام من کلارا است و من در برکلی زندگی می کنم."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_parsbert_uncased_finetuned_squad","fa") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("اسم من چیست؟", "نام من کلارا است و من در برکلی زندگی می کنم.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_parsbert_uncased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mhmsadegh/bert-base-parsbert-uncased-finetuned-squad
\ No newline at end of file

From 67fc2b2a99cc78f53b1aa23fc3bc56e15e3a5ce9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:31:50 +0700
Subject: [PATCH 003/408] Add model
 2023-11-15-bert_qa_base_pars_uncased_pquad_fa

---
 ...1-15-bert_qa_base_pars_uncased_pquad_fa.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_fa.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_fa.md
new file mode 100644
index 00000000000000..08080f3c56b3b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian BertForQuestionAnswering Base Uncased model (from mohsenfayyaz)
+author: John Snow Labs
+name: bert_qa_base_pars_uncased_pquad
+date: 2023-11-15
+tags: [fa, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-parsbert-uncased_pquad` is a Persian model originally trained by `mohsenfayyaz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_pquad_fa_5.2.0_3.0_1700058636687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_pquad_fa_5.2.0_3.0_1700058636687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_pquad","fa")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_pquad","fa")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_pars_uncased_pquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mohsenfayyaz/bert-base-parsbert-uncased_pquad
\ No newline at end of file

From c5d8d3bcfaaf34f2a589b4b4852cf79477c67f11 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:32:51 +0700
Subject: [PATCH 004/408] Add model
 2023-11-15-bert_qa_base_multilingual_cased_finetuned_xx

---
 ...qa_base_multilingual_cased_finetuned_xx.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_xx.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_xx.md
new file mode 100644
index 00000000000000..2c2b8e9f89c647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering Base Cased model (from obokkkk)
+author: John Snow Labs
+name: bert_qa_base_multilingual_cased_finetuned
+date: 2023-11-15
+tags: [xx, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetuned` is a Multilingual model originally trained by `obokkkk`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_xx_5.2.0_3.0_1700058641683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_xx_5.2.0_3.0_1700058641683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned","xx")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned","xx")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_multilingual_cased_finetuned|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/obokkkk/bert-base-multilingual-cased-finetuned
\ No newline at end of file

From af9b433153f6d068de2deed89710cd404110786e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:33:51 +0700
Subject: [PATCH 005/408] Add model
 2023-11-15-bert_qa_base_multilingual_cased_finetuned_viquad_en

---
 ..._multilingual_cased_finetuned_viquad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_viquad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_viquad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_viquad_en.md
new file mode 100644
index 00000000000000..7e94fb52721176
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_cased_finetuned_viquad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from Khanh)
+author: John Snow Labs
+name: bert_qa_base_multilingual_cased_finetuned_viquad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetuned-viquad` is a English model originally trained by `Khanh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_viquad_en_5.2.0_3.0_1700058664073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_viquad_en_5.2.0_3.0_1700058664073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned_viquad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned_viquad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.cased_multilingual_base_finetuned").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_multilingual_cased_finetuned_viquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Khanh/bert-base-multilingual-cased-finetuned-viquad
\ No newline at end of file

From f81562b8d83be27fb5d444672e260fe7cb231d19 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:34:51 +0700
Subject: [PATCH 006/408] Add model
 2023-11-15-bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en

---
 ...few_shot_k_32_finetuned_squad_seed_8_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..06bd72f330f754
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-few-shot-k-32-finetuned-squad-seed-8` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en_5.2.0_3.0_1700058852386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8_en_5.2.0_3.0_1700058852386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.uncased_seed_8_base_32d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_uncased_few_shot_k_32_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/bert-base-uncased-few-shot-k-32-finetuned-squad-seed-8
\ No newline at end of file

From de5aa6612cefa06d607b97c8d57f5bbaf04406b3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:35:51 +0700
Subject: [PATCH 007/408] Add model
 2023-11-15-bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en

---
 ...few_shot_k_64_finetuned_squad_seed_4_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..212e326ccaedc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-few-shot-k-64-finetuned-squad-seed-4` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en_5.2.0_3.0_1700058924705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4_en_5.2.0_3.0_1700058924705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.uncased_seed_4_base_64d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_uncased_few_shot_k_64_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/bert-base-uncased-few-shot-k-64-finetuned-squad-seed-4
\ No newline at end of file

From 3abde5a25343b351274d10396417077b36f46c22 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:36:52 +0700
Subject: [PATCH 008/408] Add model
 2023-11-15-bert_qa_base_nnish_cased_squad1_fi

---
 ...1-15-bert_qa_base_nnish_cased_squad1_fi.md | 96 +++++++++++++++++++
 1 file changed, 96 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_nnish_cased_squad1_fi.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_nnish_cased_squad1_fi.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_nnish_cased_squad1_fi.md
new file mode 100644
index 00000000000000..1be2a525bc4a8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_nnish_cased_squad1_fi.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: Finnish BertForQuestionAnswering Base Cased model (from ilmariky)
+author: John Snow Labs
+name: bert_qa_base_nnish_cased_squad1
+date: 2023-11-15
+tags: [fi, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fi
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-finnish-cased-squad1-fi` is a Finnish model originally trained by `ilmariky`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_nnish_cased_squad1_fi_5.2.0_3.0_1700058973995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_nnish_cased_squad1_fi_5.2.0_3.0_1700058973995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_nnish_cased_squad1","fi")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_nnish_cased_squad1","fi")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_nnish_cased_squad1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fi|
+|Size:|464.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ilmariky/bert-base-finnish-cased-squad1-fi
+- https://github.com/google-research-datasets/tydiqa
+- https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/
\ No newline at end of file

From ba8b402daf1d669c64ce7880821085bf6e818d7f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:37:52 +0700
Subject: [PATCH 009/408] Add model
 2023-11-15-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx

---
 ...ltilingual_uncased_finetuned_squadv2_xx.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx.md
new file mode 100644
index 00000000000000..bbbb2d08769c8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering Base Uncased model (from khoanvm)
+author: John Snow Labs
+name: bert_qa_base_multilingual_uncased_finetuned_squadv2
+date: 2023-11-15
+tags: [xx, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-uncased-finetuned-squadv2` is a Multilingual model originally trained by `khoanvm`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_uncased_finetuned_squadv2_xx_5.2.0_3.0_1700059023790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_uncased_finetuned_squadv2_xx_5.2.0_3.0_1700059023790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_uncased_finetuned_squadv2","xx")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_uncased_finetuned_squadv2","xx")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_multilingual_uncased_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|625.5 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/khoanvm/bert-base-multilingual-uncased-finetuned-squadv2
\ No newline at end of file

From ef9d179329c4713da9e5b0066371fcba5888145a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:38:52 +0700
Subject: [PATCH 010/408] Add model
 2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr

---
 ...d_tquad2_finetuned_lr_2e_05_epochs_3_tr.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr.md
new file mode 100644
index 00000000000000..6782fd8356d4f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish BertForQuestionAnswering Base Cased model (from husnu)
+author: John Snow Labs
+name: bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3
+date: 2023-11-15
+tags: [tr, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-turkish-128k-cased-finetuned_lr-2e-05_epochs-3TQUAD2-finetuned_lr-2e-05_epochs-3` is a Turkish model originally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr_5.2.0_3.0_1700059056675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3_tr_5.2.0_3.0_1700059056675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3","tr") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|688.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/bert-base-turkish-128k-cased-finetuned_lr-2e-05_epochs-3TQUAD2-finetuned_lr-2e-05_epochs-3
\ No newline at end of file

From 1d26b5d923b2f928fe4982fac361e0636ddac535 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:39:53 +0700
Subject: [PATCH 011/408] Add model
 2023-11-15-bert_qa_bert_all_squad_ben_tel_context_en

---
 ...rt_qa_bert_all_squad_ben_tel_context_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_ben_tel_context_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_ben_tel_context_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_ben_tel_context_en.md
new file mode 100644
index 00000000000000..c9a7bfeac9aa5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_ben_tel_context_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from krinal214)
+author: John Snow Labs
+name: bert_qa_bert_all_squad_ben_tel_context
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-all-squad_ben_tel_context` is a English model orginally trained by `krinal214`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_squad_ben_tel_context_en_5.2.0_3.0_1700059176175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_squad_ben_tel_context_en_5.2.0_3.0_1700059176175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_all_squad_ben_tel_context","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_all_squad_ben_tel_context","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad_ben_tel.bert.by_krinal214").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_all_squad_ben_tel_context|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/krinal214/bert-all-squad_ben_tel_context
\ No newline at end of file

From 269b932c2c92f1a710b6c522a737f4bdf5501749 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:40:53 +0700
Subject: [PATCH 012/408] Add model
 2023-11-15-bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en

---
 ...ed_pretrain_finetuned_coqa_falttened_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en.md
new file mode 100644
index 00000000000000..94e76549a838a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from alistvt)
+author: John Snow Labs
+name: bert_qa_base_uncased_pretrain_finetuned_coqa_falttened
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-pretrain-finetuned-coqa-falttened` is a English model originally trained by `alistvt`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en_5.2.0_3.0_1700059206672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_pretrain_finetuned_coqa_falttened_en_5.2.0_3.0_1700059206672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_pretrain_finetuned_coqa_falttened","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_pretrain_finetuned_coqa_falttened","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.uncased_base_finetuned.by_alistvt").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_uncased_pretrain_finetuned_coqa_falttened|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/alistvt/bert-base-uncased-pretrain-finetuned-coqa-falttened
\ No newline at end of file

From 96f7fe61b6939f6a4fa2877695c1170fef89aacd Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:41:53 +0700
Subject: [PATCH 013/408] Add model 2023-11-15-bert_qa_bert_all_en

---
 .../2023-11-15-bert_qa_bert_all_en.md         | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_en.md
new file mode 100644
index 00000000000000..9e4f59fdbb84df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from krinal214)
+author: John Snow Labs
+name: bert_qa_bert_all
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-all` is a English model orginally trained by `krinal214`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_en_5.2.0_3.0_1700059293524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_en_5.2.0_3.0_1700059293524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_all","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_all","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.tydiqa.bert").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_all|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/krinal214/bert-all
\ No newline at end of file

From 07a6a188b57036df1a921c6f1015d5090696a582 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:43:54 +0700
Subject: [PATCH 014/408] Add model
 2023-11-15-bert_qa_base_pars_uncased_parsquad_fa

---
 ...5-bert_qa_base_pars_uncased_parsquad_fa.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_parsquad_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_parsquad_fa.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_parsquad_fa.md
new file mode 100644
index 00000000000000..b31cf443f85fc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_parsquad_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian BertForQuestionAnswering Base Uncased model (from mohsenfayyaz)
+author: John Snow Labs
+name: bert_qa_base_pars_uncased_parsquad
+date: 2023-11-15
+tags: [fa, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-parsbert-uncased_parsquad` is a Persian model originally trained by `mohsenfayyaz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_parsquad_fa_5.2.0_3.0_1700059423764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_parsquad_fa_5.2.0_3.0_1700059423764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_parsquad","fa")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_parsquad","fa")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_pars_uncased_parsquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mohsenfayyaz/bert-base-parsbert-uncased_parsquad
\ No newline at end of file

From 19bddd46000ca0e991238b48c5a591facb23d85a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:44:54 +0700
Subject: [PATCH 015/408] Add model 2023-11-15-bert_qa_bert_all_translated_en

---
 ...23-11-15-bert_qa_bert_all_translated_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_translated_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_translated_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_translated_en.md
new file mode 100644
index 00000000000000..4e140ac105330c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_translated_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from krinal214)
+author: John Snow Labs
+name: bert_qa_bert_all_translated
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-all-translated` is a English model orginally trained by `krinal214`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_translated_en_5.2.0_3.0_1700059452244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_translated_en_5.2.0_3.0_1700059452244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_all_translated","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_all_translated","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.by_krinal214").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_all_translated|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/krinal214/bert-all-translated
\ No newline at end of file

From 64550d6a5ea06d95db39e541cd75c83391811f98 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:45:58 +0700
Subject: [PATCH 016/408] Add model
 2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta

---
 ...e_multilingual_cased_finetuned_chaii_ta.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta.md
new file mode 100644
index 00000000000000..e2314f5e6a17f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Tamil BertForQuestionAnswering model (from SauravMaheshkar)
+author: John Snow Labs
+name: bert_qa_bert_base_multilingual_cased_finetuned_chaii
+date: 2023-11-15
+tags: [open_source, question_answering, bert, ta, onnx]
+task: Question Answering
+language: ta
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetuned-chaii` is a Tamil model orginally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta_5.2.0_3.0_1700059545429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_finetuned_chaii_ta_5.2.0_3.0_1700059545429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_multilingual_cased_finetuned_chaii","ta") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_multilingual_cased_finetuned_chaii","ta")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ta.answer_question.chaii.bert.multilingual_base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_multilingual_cased_finetuned_chaii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|ta|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/bert-base-multilingual-cased-finetuned-chaii
\ No newline at end of file

From fff27a01712dd5ab97f5b754d238c1b324e469da Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:46:58 +0700
Subject: [PATCH 017/408] Add model
 2023-11-15-bert_qa_bert_base_multilingual_cased_finetune_qa_th

---
 ..._base_multilingual_cased_finetune_qa_th.md | 110 ++++++++++++++++++
 1 file changed, 110 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetune_qa_th.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetune_qa_th.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetune_qa_th.md
new file mode 100644
index 00000000000000..b94f2ab8cd78eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetune_qa_th.md
@@ -0,0 +1,110 @@
+---
+layout: model
+title: Thai BertForQuestionAnswering model (from airesearch)
+author: John Snow Labs
+name: bert_qa_bert_base_multilingual_cased_finetune_qa
+date: 2023-11-15
+tags: [th, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: th
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetune-qa` is a Thai model orginally trained by `airesearch`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_finetune_qa_th_5.2.0_3.0_1700059563752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_finetune_qa_th_5.2.0_3.0_1700059563752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_multilingual_cased_finetune_qa","th") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_multilingual_cased_finetune_qa","th")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("th.answer_question.bert.multilingual_base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_multilingual_cased_finetune_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|th|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/airesearch/bert-base-multilingual-cased-finetune-qa
+- https://github.com/vistec-AI/thai2transformers/blob/dev/scripts/downstream/train_question_answering_lm_finetuning.py
+- https://wandb.ai/cstorm125/wangchanberta-qa
\ No newline at end of file

From 0a06c99943372d68b73597534f96c639b04eff73 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:47:58 +0700
Subject: [PATCH 018/408] Add model
 2023-11-15-bert_qa_bert_all_squad_all_translated_en

---
 ...ert_qa_bert_all_squad_all_translated_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_all_translated_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_all_translated_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_all_translated_en.md
new file mode 100644
index 00000000000000..1da871f8043223
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_all_translated_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from krinal214)
+author: John Snow Labs
+name: bert_qa_bert_all_squad_all_translated
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-all-squad_all_translated` is a English model orginally trained by `krinal214`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_squad_all_translated_en_5.2.0_3.0_1700059641983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_squad_all_translated_en_5.2.0_3.0_1700059641983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_all_squad_all_translated","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_all_squad_all_translated","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad_translated.bert.by_krinal214").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_all_squad_all_translated|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/krinal214/bert-all-squad_all_translated
\ No newline at end of file

From 69cd6540dfd33c52a7fbc497e4ea0041b691bbf0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:48:59 +0700
Subject: [PATCH 019/408] Add model 2023-11-15-bert_qa_bert_base_cased_chaii_en

---
 ...-11-15-bert_qa_bert_base_cased_chaii_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_cased_chaii_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_cased_chaii_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_cased_chaii_en.md
new file mode 100644
index 00000000000000..b785051d9818a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_cased_chaii_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from SauravMaheshkar)
+author: John Snow Labs
+name: bert_qa_bert_base_cased_chaii
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-cased-chaii` is a English model orginally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_cased_chaii_en_5.2.0_3.0_1700059727653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_cased_chaii_en_5.2.0_3.0_1700059727653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_cased_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_cased_chaii","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.bert.base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_cased_chaii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/bert-base-cased-chaii
\ No newline at end of file

From 5eb2e766125565db5d5a98994cd7433f0e222836 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:49:59 +0700
Subject: [PATCH 020/408] Add model
 2023-11-15-bert_qa_base_pars_uncased_pquad_1epoch_fa

---
 ...rt_qa_base_pars_uncased_pquad_1epoch_fa.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_1epoch_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_1epoch_fa.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_1epoch_fa.md
new file mode 100644
index 00000000000000..104033122180e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_1epoch_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian BertForQuestionAnswering Base Uncased model (from mohsenfayyaz)
+author: John Snow Labs
+name: bert_qa_base_pars_uncased_pquad_1epoch
+date: 2023-11-15
+tags: [fa, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-parsbert-uncased_pquad_1epoch` is a Persian model originally trained by `mohsenfayyaz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_pquad_1epoch_fa_5.2.0_3.0_1700059740761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_pquad_1epoch_fa_5.2.0_3.0_1700059740761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_pquad_1epoch","fa")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_pquad_1epoch","fa")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_pars_uncased_pquad_1epoch|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mohsenfayyaz/bert-base-parsbert-uncased_pquad_1epoch
\ No newline at end of file

From 1948f7edae26f35285ba617309b36d1b3ef7bfee Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:50:59 +0700
Subject: [PATCH 021/408] Add model
 2023-11-15-bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en

---
 ...base_uncased_squad2_covid_qa_deepset_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en.md
new file mode 100644
index 00000000000000..7ed52bfb2b4b35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from armageddon)
+author: John Snow Labs
+name: bert_qa_bert_base_uncased_squad2_covid_qa_deepset
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-squad2-covid-qa-deepset` is a English model orginally trained by `armageddon`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en_5.2.0_3.0_1700059817938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_uncased_squad2_covid_qa_deepset_en_5.2.0_3.0_1700059817938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_uncased_squad2_covid_qa_deepset","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_uncased_squad2_covid_qa_deepset","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2_covid.bert.base_uncased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_uncased_squad2_covid_qa_deepset|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/armageddon/bert-base-uncased-squad2-covid-qa-deepset
\ No newline at end of file

From 3a50deab67d51e4218f02f8162f9619302737ed0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:52:00 +0700
Subject: [PATCH 022/408] Add model
 2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es

---
 ..._spanish_wwm_cased_finetuned_qa_sqac_es.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es.md
new file mode 100644
index 00000000000000..5dcea721431a84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Castilian, Spanish BertForQuestionAnswering model (from CenIA)
+author: John Snow Labs
+name: bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac
+date: 2023-11-15
+tags: [open_source, question_answering, bert, es, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-spanish-wwm-cased-finetuned-qa-sqac` is a Castilian, Spanish model orginally trained by `CenIA`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es_5.2.0_3.0_1700059818270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac_es_5.2.0_3.0_1700059818270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac","es") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac","es")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.answer_question.sqac.bert.base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_sqac|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|es|
+|Size:|409.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/CenIA/bert-base-spanish-wwm-cased-finetuned-qa-sqac
\ No newline at end of file

From af71d7d66f92853d8bf194e912d1df8d0010f52f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:53:00 +0700
Subject: [PATCH 023/408] Add model 2023-11-15-bert_qa_bert_base_faquad_en

---
 .../2023-11-15-bert_qa_bert_base_faquad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_faquad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_faquad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_faquad_en.md
new file mode 100644
index 00000000000000..b2309b202800b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_faquad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from ricardo-filho)
+author: John Snow Labs
+name: bert_qa_bert_base_faquad
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_base_faquad` is a English model orginally trained by `ricardo-filho`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_faquad_en_5.2.0_3.0_1700059918542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_faquad_en_5.2.0_3.0_1700059918542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_faquad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_faquad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_faquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|405.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ricardo-filho/bert_base_faquad
\ No newline at end of file

From 8ed745dd9de3b068cf451982a2289d3b40b5010d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:54:34 +0700
Subject: [PATCH 024/408] Add model
 2023-11-15-bert_qa_base_pars_uncased_pquad_lr1e_5_fa

---
 ...rt_qa_base_pars_uncased_pquad_lr1e_5_fa.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_lr1e_5_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_lr1e_5_fa.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_lr1e_5_fa.md
new file mode 100644
index 00000000000000..99a2e56652a587
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_pars_uncased_pquad_lr1e_5_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian BertForQuestionAnswering Base Uncased model (from mohsenfayyaz)
+author: John Snow Labs
+name: bert_qa_base_pars_uncased_pquad_lr1e_5
+date: 2023-11-15
+tags: [fa, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-parsbert-uncased_pquad_lr1e-5` is a Persian model originally trained by `mohsenfayyaz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_pquad_lr1e_5_fa_5.2.0_3.0_1700060064612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_pars_uncased_pquad_lr1e_5_fa_5.2.0_3.0_1700060064612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_pquad_lr1e_5","fa")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_pars_uncased_pquad_lr1e_5","fa")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_pars_uncased_pquad_lr1e_5|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mohsenfayyaz/bert-base-parsbert-uncased_pquad_lr1e-5
\ No newline at end of file

From aeb9ebae4578b3770669ce566d195abfac6a7eca Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:55:34 +0700
Subject: [PATCH 025/408] Add model
 2023-11-15-bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr

---
 ...sh_cased_finetuned_lr_2e_05_epochs_3_tr.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr.md
new file mode 100644
index 00000000000000..3622d66291aa6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Turkish BertForQuestionAnswering model (from husnu)
+author: John Snow Labs
+name: bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3
+date: 2023-11-15
+tags: [open_source, question_answering, bert, tr, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-turkish-cased-finetuned_lr-2e-05_epochs-3` is a Turkish model orginally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr_5.2.0_3.0_1700060105366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3_tr_5.2.0_3.0_1700060105366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3","tr") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3","tr")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("tr.answer_question.bert.base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_turkish_cased_finetuned_lr_2e_05_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|tr|
+|Size:|412.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/bert-base-turkish-cased-finetuned_lr-2e-05_epochs-3
\ No newline at end of file

From 39bbafd2cdaa7cf79e063a72d984034fcd4f42e0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:56:35 +0700
Subject: [PATCH 026/408] Add model
 2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_klue_ko

---
 ...se_multilingual_cased_finetuned_klue_ko.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_klue_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_klue_ko.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_klue_ko.md
new file mode 100644
index 00000000000000..fe5d082c26cad3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_finetuned_klue_ko.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Korean BertForQuestionAnswering model (from obokkkk)
+author: John Snow Labs
+name: bert_qa_bert_base_multilingual_cased_finetuned_klue
+date: 2023-11-15
+tags: [open_source, question_answering, bert, ko, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetuned-klue` is a Korean model orginally trained by `obokkkk`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_finetuned_klue_ko_5.2.0_3.0_1700060100566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_finetuned_klue_ko_5.2.0_3.0_1700060100566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_multilingual_cased_finetuned_klue","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_multilingual_cased_finetuned_klue","ko")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.klue.bert.multilingual_base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_multilingual_cased_finetuned_klue|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|ko|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/obokkkk/bert-base-multilingual-cased-finetuned-klue
\ No newline at end of file

From 58dcee071b549cd96045ad13feb1ec8c277e5b1a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 21:58:40 +0700
Subject: [PATCH 027/408] Add model
 2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_ko

---
 ...bert_base_multilingual_cased_korquad_ko.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_ko.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_ko.md
new file mode 100644
index 00000000000000..fae9a84c7b301c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_ko.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Korean BertForQuestionAnswering model (from sangrimlee)
+author: John Snow Labs
+name: bert_qa_bert_base_multilingual_cased_korquad
+date: 2023-11-15
+tags: [open_source, question_answering, bert, ko, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-korquad` is a Korean model orginally trained by `sangrimlee`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_korquad_ko_5.2.0_3.0_1700060305908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_korquad_ko_5.2.0_3.0_1700060305908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_multilingual_cased_korquad","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_multilingual_cased_korquad","ko")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.korquad.bert.multilingual_base_cased.by_sangrimlee").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_multilingual_cased_korquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|ko|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/sangrimlee/bert-base-multilingual-cased-korquad
\ No newline at end of file

From e3fa87c67a66b2df8f5e4a5d96c8153620902714 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:00:08 +0700
Subject: [PATCH 028/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en

---
 ...arge_uncased_squad2_covid_qa_deepset_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en.md
new file mode 100644
index 00000000000000..5d66bcd0b1d283
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from armageddon)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_squad2_covid_qa_deepset
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-squad2-covid-qa-deepset` is a English model orginally trained by `armageddon`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en_5.2.0_3.0_1700060388720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_squad2_covid_qa_deepset_en_5.2.0_3.0_1700060388720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_squad2_covid_qa_deepset","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_squad2_covid_qa_deepset","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2_covid.bert.large_uncased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_squad2_covid_qa_deepset|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/armageddon/bert-large-uncased-squad2-covid-qa-deepset
\ No newline at end of file

From 6130dac3041ab8c7940c6086007d70f3a91a49a1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:01:08 +0700
Subject: [PATCH 029/408] Add model
 2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr

---
 ...d_tquad2_finetuned_lr_2e_05_epochs_1_tr.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr.md
new file mode 100644
index 00000000000000..c1cd39c000eab9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish BertForQuestionAnswering Base Cased model (from husnu)
+author: John Snow Labs
+name: bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1
+date: 2023-11-15
+tags: [tr, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-turkish-128k-cased-finetuned_lr-2e-05_epochs-3TQUAD2-finetuned_lr-2e-05_epochs-1` is a Turkish model originally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr_5.2.0_3.0_1700060421173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1_tr_5.2.0_3.0_1700060421173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1","tr") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_turkish_128k_cased_tquad2_finetuned_lr_2e_05_epochs_1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|688.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/bert-base-turkish-128k-cased-finetuned_lr-2e-05_epochs-3TQUAD2-finetuned_lr-2e-05_epochs-1
\ No newline at end of file

From 8545fee7221b6153d6fc5ed45a11c260e2ede260 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:02:08 +0700
Subject: [PATCH 030/408] Add model
 2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_v1_ko

---
 ...t_base_multilingual_cased_korquad_v1_ko.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_v1_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_v1_ko.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_v1_ko.md
new file mode 100644
index 00000000000000..93bd3a5f8018f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_cased_korquad_v1_ko.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Korean BertForQuestionAnswering model (from eliza-dukim)
+author: John Snow Labs
+name: bert_qa_bert_base_multilingual_cased_korquad_v1
+date: 2023-11-15
+tags: [open_source, question_answering, bert, ko, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased_korquad-v1` is a Korean model orginally trained by `eliza-dukim`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_korquad_v1_ko_5.2.0_3.0_1700060432159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_cased_korquad_v1_ko_5.2.0_3.0_1700060432159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_multilingual_cased_korquad_v1","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_multilingual_cased_korquad_v1","ko")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.korquad.bert.multilingual_base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_multilingual_cased_korquad_v1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|ko|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/eliza-dukim/bert-base-multilingual-cased_korquad-v1
\ No newline at end of file

From afb59396569cdf0c25c8a5adc72a0729b9db2eff Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:04:08 +0700
Subject: [PATCH 031/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_squad2_en

---
 ...ge_uncased_whole_word_masking_squad2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_squad2_en.md
new file mode 100644
index 00000000000000..726df0b4226947
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_squad2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from deepset)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_whole_word_masking_squad2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-whole-word-masking-squad2` is a English model orginally trained by `deepset`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_squad2_en_5.2.0_3.0_1700060629483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_squad2_en_5.2.0_3.0_1700060629483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_whole_word_masking_squad2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_whole_word_masking_squad2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.large_uncased.by_deepset").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_whole_word_masking_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/bert-large-uncased-whole-word-masking-squad2
\ No newline at end of file

From 1c1329c09c0e798fa9a6a57a952f8ba8d8474cdc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:05:08 +0700
Subject: [PATCH 032/408] Add model
 2023-11-15-bert_qa_bert_base_multilingual_xquad_xx

---
 ...bert_qa_bert_base_multilingual_xquad_xx.md | 109 ++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_xquad_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_xquad_xx.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_xquad_xx.md
new file mode 100644
index 00000000000000..8fb375399347eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_multilingual_xquad_xx.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering model (from alon-albalak)
+author: John Snow Labs
+name: bert_qa_bert_base_multilingual_xquad
+date: 2023-11-15
+tags: [open_source, question_answering, bert, xx, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-xquad` is a Multilingual model orginally trained by `alon-albalak`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_xquad_xx_5.2.0_3.0_1700060659109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_multilingual_xquad_xx_5.2.0_3.0_1700060659109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_multilingual_xquad","xx") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_multilingual_xquad","xx")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("xx.answer_question.xquad.bert.multilingual_base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_multilingual_xquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|625.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/alon-albalak/bert-base-multilingual-xquad
+- https://github.com/deepmind/xquad
\ No newline at end of file

From 553542b0f565f4e4e1a36e97ae127d8fa33d8d54 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:06:09 +0700
Subject: [PATCH 033/408] Add model
 2023-11-15-bert_qa_bert_finetuned_jackh1995_en

---
 ...-15-bert_qa_bert_finetuned_jackh1995_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_jackh1995_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_jackh1995_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_jackh1995_en.md
new file mode 100644
index 00000000000000..2972ffc17097ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_jackh1995_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from jackh1995)
+author: John Snow Labs
+name: bert_qa_bert_finetuned_jackh1995
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned` is a English model orginally trained by `jackh1995`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_finetuned_jackh1995_en_5.2.0_3.0_1700060719811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_finetuned_jackh1995_en_5.2.0_3.0_1700060719811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_finetuned_jackh1995","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_finetuned_jackh1995","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.by_jackh1995").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_finetuned_jackh1995|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|380.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/jackh1995/bert-finetuned
\ No newline at end of file

From 956a35e62e5cf32393428ea76024ea03ea6e8710 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:07:09 +0700
Subject: [PATCH 034/408] Add model
 2023-11-15-bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en

---
 ...ew_shot_k_128_finetuned_squad_seed_2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..1c4e851167f44d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-few-shot-k-128-finetuned-squad-seed-2` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en_5.2.0_3.0_1700060723604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2_en_5.2.0_3.0_1700060723604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.uncased_seed_2_base_128d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_uncased_few_shot_k_128_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/bert-base-uncased-few-shot-k-128-finetuned-squad-seed-2
\ No newline at end of file

From cd22b15a8f847303b6f4ede28b8c5a98c0862af9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:08:26 +0700
Subject: [PATCH 035/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en

---
 ...uadv1.1_sparse_80_1x4_block_pruneofa_en.md | 110 ++++++++++++++++++
 1 file changed, 110 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en.md
new file mode 100644
index 00000000000000..c73276c9e15a45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en.md
@@ -0,0 +1,110 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from Intel)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-squadv1.1-sparse-80-1x4-block-pruneofa` is a English model orginally trained by `Intel`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en_5.2.0_3.0_1700060896462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa_en_5.2.0_3.0_1700060896462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.large_uncased_sparse_80_1x4_block_pruneofa.by_Intel").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_squadv1.1_sparse_80_1x4_block_pruneofa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|436.9 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Intel/bert-large-uncased-squadv1.1-sparse-80-1x4-block-pruneofa
+- https://arxiv.org/abs/2111.05754
+- https://github.com/IntelLabs/Model-Compression-Research-Package/tree/main/research/prune-once-for-all
\ No newline at end of file

From cb5948a96454b5890ae40e5b0f67e9b941d2da60 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:09:27 +0700
Subject: [PATCH 036/408] Add model
 2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es

---
 ..._spanish_wwm_cased_finetuned_qa_mlqa_es.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es.md
new file mode 100644
index 00000000000000..319f983b4e15e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Castilian, Spanish BertForQuestionAnswering model (from CenIA)
+author: John Snow Labs
+name: bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa
+date: 2023-11-15
+tags: [open_source, question_answering, bert, es, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-spanish-wwm-cased-finetuned-qa-mlqa` is a Castilian, Spanish model orginally trained by `CenIA`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es_5.2.0_3.0_1700060933708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa_es_5.2.0_3.0_1700060933708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa","es") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa","es")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.answer_question.mlqa.bert.base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_spanish_wwm_cased_finetuned_qa_mlqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|es|
+|Size:|409.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/CenIA/bert-base-spanish-wwm-cased-finetuned-qa-mlqa
\ No newline at end of file

From 71fc1eabe3688fd5a950e80d5ba1dba6d9024a66 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:10:27 +0700
Subject: [PATCH 037/408] Add model
 2023-11-15-bert_qa_bert_multi_english_german_squad2_de

---
 ..._qa_bert_multi_english_german_squad2_de.md | 110 ++++++++++++++++++
 1 file changed, 110 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_english_german_squad2_de.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_english_german_squad2_de.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_english_german_squad2_de.md
new file mode 100644
index 00000000000000..2233512e19029d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_english_german_squad2_de.md
@@ -0,0 +1,110 @@
+---
+layout: model
+title: German BertForQuestionAnswering model (from deutsche-telekom)
+author: John Snow Labs
+name: bert_qa_bert_multi_english_german_squad2
+date: 2023-11-15
+tags: [de, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: de
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-multi-english-german-squad2` is a German model orginally trained by `deutsche-telekom`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_english_german_squad2_de_5.2.0_3.0_1700060982961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_english_german_squad2_de_5.2.0_3.0_1700060982961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_multi_english_german_squad2","de") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_multi_english_german_squad2","de")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.answer_question.squadv2.bert").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_multi_english_german_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/deutsche-telekom/bert-multi-english-german-squad2
+- https://rajpurkar.github.io/SQuAD-explorer/
+- https://github.com/google-research/bert/blob/master/multilingual.md
\ No newline at end of file

From d9364b8d8082eb8e3eda707998e7b11feacdb248 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:11:27 +0700
Subject: [PATCH 038/408] Add model
 2023-11-15-bert_qa_bert_finetuned_lr2_e5_b16_ep2_en

---
 ...ert_qa_bert_finetuned_lr2_e5_b16_ep2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_lr2_e5_b16_ep2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_lr2_e5_b16_ep2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_lr2_e5_b16_ep2_en.md
new file mode 100644
index 00000000000000..be38585f77da4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_finetuned_lr2_e5_b16_ep2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from motiondew)
+author: John Snow Labs
+name: bert_qa_bert_finetuned_lr2_e5_b16_ep2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-lr2-e5-b16-ep2` is a English model orginally trained by `motiondew`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_finetuned_lr2_e5_b16_ep2_en_5.2.0_3.0_1700061010799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_finetuned_lr2_e5_b16_ep2_en_5.2.0_3.0_1700061010799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_finetuned_lr2_e5_b16_ep2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_finetuned_lr2_e5_b16_ep2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.by_motiondew").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_finetuned_lr2_e5_b16_ep2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/motiondew/bert-finetuned-lr2-e5-b16-ep2
\ No newline at end of file

From 0870396ee772053dda1b7139bea6b1d6d4640846 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:12:27 +0700
Subject: [PATCH 039/408] Add model
 2023-11-15-bert_qa_bdickson_bert_base_uncased_finetuned_squad_en

---
 ...on_bert_base_uncased_finetuned_squad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bdickson_bert_base_uncased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bdickson_bert_base_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bdickson_bert_base_uncased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..17a76e335616b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bdickson_bert_base_uncased_finetuned_squad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from bdickson)
+author: John Snow Labs
+name: bert_qa_bdickson_bert_base_uncased_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-finetuned-squad` is a English model orginally trained by `bdickson`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bdickson_bert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700061010787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bdickson_bert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700061010787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bdickson_bert_base_uncased_finetuned_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bdickson_bert_base_uncased_finetuned_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.base_uncased.by_bdickson").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bdickson_bert_base_uncased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/bdickson/bert-base-uncased-finetuned-squad
\ No newline at end of file

From 930d5dfd81cfa040f9ca363ec546048eb8905ca6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:13:38 +0700
Subject: [PATCH 040/408] Add model
 2023-11-15-bert_qa_bert_base_uncased_coqa_en

---
 ...11-15-bert_qa_bert_base_uncased_coqa_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_coqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_coqa_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_coqa_en.md
new file mode 100644
index 00000000000000..3ef3e5f157d50a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_uncased_coqa_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from peggyhuang)
+author: John Snow Labs
+name: bert_qa_bert_base_uncased_coqa
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-coqa` is a English model orginally trained by `peggyhuang`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_uncased_coqa_en_5.2.0_3.0_1700061211300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_uncased_coqa_en_5.2.0_3.0_1700061211300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_uncased_coqa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_uncased_coqa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.base_uncased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_uncased_coqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/peggyhuang/bert-base-uncased-coqa
\ No newline at end of file

From e1c06fe27810a0bafffe64b2f14c5ccf8d4164fa Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:16:13 +0700
Subject: [PATCH 041/408] Add model
 2023-11-15-bert_qa_biobertpt_squad_v1.1_portuguese_pt

---
 ...t_qa_biobertpt_squad_v1.1_portuguese_pt.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_biobertpt_squad_v1.1_portuguese_pt.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_biobertpt_squad_v1.1_portuguese_pt.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_biobertpt_squad_v1.1_portuguese_pt.md
new file mode 100644
index 00000000000000..b3b73c5151a2f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_biobertpt_squad_v1.1_portuguese_pt.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: Portuguese bert_qa_biobertpt_squad_v1.1_portuguese BertForQuestionAnswering from pucpr
+author: John Snow Labs
+name: bert_qa_biobertpt_squad_v1.1_portuguese
+date: 2023-11-15
+tags: [bert, pt, open_source, question_answering, onnx]
+task: Question Answering
+language: pt
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_biobertpt_squad_v1.1_portuguese` is a Portuguese model originally trained by pucpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_biobertpt_squad_v1.1_portuguese_pt_5.2.0_3.0_1700061364212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_biobertpt_squad_v1.1_portuguese_pt_5.2.0_3.0_1700061364212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_biobertpt_squad_v1.1_portuguese","pt") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_biobertpt_squad_v1.1_portuguese", "pt")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_biobertpt_squad_v1.1_portuguese|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|664.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/pucpr/bioBERTpt-squad-v1.1-portuguese
\ No newline at end of file

From 5215ca05127287dca3dc4df15378c50d96e9592d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:17:13 +0700
Subject: [PATCH 042/408] Add model
 2023-11-15-bert_qa_bert_all_squad_que_translated_en

---
 ...ert_qa_bert_all_squad_que_translated_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_que_translated_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_que_translated_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_que_translated_en.md
new file mode 100644
index 00000000000000..379dda9a170506
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_all_squad_que_translated_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from krinal214)
+author: John Snow Labs
+name: bert_qa_bert_all_squad_que_translated
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-all-squad_que_translated` is a English model orginally trained by `krinal214`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_squad_que_translated_en_5.2.0_3.0_1700061367686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_all_squad_que_translated_en_5.2.0_3.0_1700061367686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_all_squad_que_translated","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_all_squad_que_translated","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad_translated.bert.que.by_krinal214").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_all_squad_que_translated|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/krinal214/bert-all-squad_que_translated
\ No newline at end of file

From a187e8ac2701c2c3ab4f83847b78c807d3c19cc4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:19:31 +0700
Subject: [PATCH 043/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_squadv2_en

---
 ...5-bert_qa_bert_large_uncased_squadv2_en.md | 109 ++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv2_en.md
new file mode 100644
index 00000000000000..1de5303da08fcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_squadv2_en.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from madlag)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_squadv2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-squadv2` is a English model orginally trained by `madlag`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_squadv2_en_5.2.0_3.0_1700061553399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_squadv2_en_5.2.0_3.0_1700061553399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_squadv2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_squadv2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.large_uncased_v2.by_madlag").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/madlag/bert-large-uncased-squadv2
+- https://arxiv.org/pdf/1810.04805v2.pdf%5D
\ No newline at end of file

From e91ffa615b9eb8f0c15fe28f1f179aace2f187c1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:20:31 +0700
Subject: [PATCH 044/408] Add model 2023-11-15-bert_qa_bertfast_01_en

---
 .../2023-11-15-bert_qa_bertfast_01_en.md      | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertfast_01_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertfast_01_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertfast_01_en.md
new file mode 100644
index 00000000000000..5c84066b3a080b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertfast_01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from JAlexis)
+author: John Snow Labs
+name: bert_qa_bertfast_01
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bertFast_01` is a English model originally trained by `JAlexis`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bertfast_01_en_5.2.0_3.0_1700061584041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bertfast_01_en_5.2.0_3.0_1700061584041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_bertfast_01","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_bertfast_01","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bertfast_01|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/JAlexis/bertFast_01
\ No newline at end of file

From 96898dbaf6c466c328eb4215e87f7a00eeedca2c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:21:32 +0700
Subject: [PATCH 045/408] Add model
 2023-11-15-bert_qa_biomedical_slot_filling_reader_base_en

---
 ..._biomedical_slot_filling_reader_base_en.md | 109 ++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_biomedical_slot_filling_reader_base_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_biomedical_slot_filling_reader_base_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_biomedical_slot_filling_reader_base_en.md
new file mode 100644
index 00000000000000..4af56e67551eef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_biomedical_slot_filling_reader_base_en.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from healx)
+author: John Snow Labs
+name: bert_qa_biomedical_slot_filling_reader_base
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `biomedical-slot-filling-reader-base` is a English model orginally trained by `healx`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_biomedical_slot_filling_reader_base_en_5.2.0_3.0_1700061626085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_biomedical_slot_filling_reader_base_en_5.2.0_3.0_1700061626085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_biomedical_slot_filling_reader_base","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_biomedical_slot_filling_reader_base","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bio_medical.bert.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_biomedical_slot_filling_reader_base|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/healx/biomedical-slot-filling-reader-base
+- https://arxiv.org/abs/2109.08564
\ No newline at end of file

From 21867543270f0c1587f85c1d0034e6f467ef89d2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:22:32 +0700
Subject: [PATCH 046/408] Add model
 2023-11-15-bert_qa_bert_base_2048_full_trivia_copied_embeddings_en

---
 ...e_2048_full_trivia_copied_embeddings_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_2048_full_trivia_copied_embeddings_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_2048_full_trivia_copied_embeddings_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_2048_full_trivia_copied_embeddings_en.md
new file mode 100644
index 00000000000000..1f7fef1dae86ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_base_2048_full_trivia_copied_embeddings_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from MrAnderson)
+author: John Snow Labs
+name: bert_qa_bert_base_2048_full_trivia_copied_embeddings
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-2048-full-trivia-copied-embeddings` is a English model orginally trained by `MrAnderson`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_2048_full_trivia_copied_embeddings_en_5.2.0_3.0_1700061631557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_base_2048_full_trivia_copied_embeddings_en_5.2.0_3.0_1700061631557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_base_2048_full_trivia_copied_embeddings","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_base_2048_full_trivia_copied_embeddings","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.trivia.bert.base_2048.by_MrAnderson").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_base_2048_full_trivia_copied_embeddings|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|411.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/MrAnderson/bert-base-2048-full-trivia-copied-embeddings
\ No newline at end of file

From c94aa16ecf8586ea7a7679cb955ae257fad2096b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:23:32 +0700
Subject: [PATCH 047/408] Add model
 2023-11-15-bert_qa_bert_l_squadv1.1_sl256_en

---
 ...11-15-bert_qa_bert_l_squadv1.1_sl256_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl256_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl256_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl256_en.md
new file mode 100644
index 00000000000000..af68cdbbb6a27f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl256_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from vuiseng9)
+author: John Snow Labs
+name: bert_qa_bert_l_squadv1.1_sl256
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-l-squadv1.1-sl256` is a English model orginally trained by `vuiseng9`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_l_squadv1.1_sl256_en_5.2.0_3.0_1700061732088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_l_squadv1.1_sl256_en_5.2.0_3.0_1700061732088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_l_squadv1.1_sl256","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_l_squadv1.1_sl256","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.sl256.by_vuiseng9").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_l_squadv1.1_sl256|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/vuiseng9/bert-l-squadv1.1-sl256
\ No newline at end of file

From a59d729520b36067dd367b39306fa19fbbfeda46 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:26:45 +0700
Subject: [PATCH 048/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en

---
 ...w_shot_k_128_finetuned_squad_seed_10_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en.md
new file mode 100644
index 00000000000000..d0c47898e73899
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-10` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en_5.2.0_3.0_1700061998255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10_en_5.2.0_3.0_1700061998255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_128d_seed_10").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|380.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-10
\ No newline at end of file

From e9420b0e7583a4cee076c90cf4d283bc42a6ce9b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:31:04 +0700
Subject: [PATCH 049/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_chaii_en

---
 ...rge_uncased_whole_word_masking_chaii_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_chaii_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_chaii_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_chaii_en.md
new file mode 100644
index 00000000000000..63dde9a6bf3349
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_chaii_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from SauravMaheshkar)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_whole_word_masking_chaii
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-whole-word-masking-chaii` is a English model orginally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_chaii_en_5.2.0_3.0_1700062243886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_chaii_en_5.2.0_3.0_1700062243886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_whole_word_masking_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_whole_word_masking_chaii","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.bert.large_uncased_uncased_whole_word_masking.by_SauravMaheshkar").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_whole_word_masking_chaii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/bert-large-uncased-whole-word-masking-chaii
\ No newline at end of file

From 6396c61b582937e5623f066edbdf7f5f2872640e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:32:27 +0700
Subject: [PATCH 050/408] Add model 2023-11-15-bert_qa_bertimbau_squad1.1_en

---
 ...023-11-15-bert_qa_bertimbau_squad1.1_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertimbau_squad1.1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertimbau_squad1.1_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertimbau_squad1.1_en.md
new file mode 100644
index 00000000000000..bb343a2af85660
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertimbau_squad1.1_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from hendrixcosta)
+author: John Snow Labs
+name: bert_qa_bertimbau_squad1.1
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bertimbau-squad1.1` is a English model orginally trained by `hendrixcosta`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bertimbau_squad1.1_en_5.2.0_3.0_1700062328092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bertimbau_squad1.1_en_5.2.0_3.0_1700062328092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bertimbau_squad1.1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bertimbau_squad1.1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.by_hendrixcosta").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bertimbau_squad1.1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/hendrixcosta/bertimbau-squad1.1
\ No newline at end of file

From 2e807238af1da8d1b4863df166ce96b40f0044d2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:33:27 +0700
Subject: [PATCH 051/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en

---
 ...few_shot_k_16_finetuned_squad_seed_6_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..7d24bb9bc8a33a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-6` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en_5.2.0_3.0_1700062364295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6_en_5.2.0_3.0_1700062364295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_6_base_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|375.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-6
\ No newline at end of file

From f5e1f2c7632e4b014af24eaf53723b7f675b4cf3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:34:27 +0700
Subject: [PATCH 052/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_finetuned_docvqa_en

---
 ..._bert_large_uncased_finetuned_docvqa_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_finetuned_docvqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_finetuned_docvqa_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_finetuned_docvqa_en.md
new file mode 100644
index 00000000000000..c7a148568b920e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_finetuned_docvqa_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from tiennvcs)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_finetuned_docvqa
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-finetuned-docvqa` is a English model orginally trained by `tiennvcs`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_finetuned_docvqa_en_5.2.0_3.0_1700062342574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_finetuned_docvqa_en_5.2.0_3.0_1700062342574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_finetuned_docvqa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_finetuned_docvqa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.large_uncased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_finetuned_docvqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/tiennvcs/bert-large-uncased-finetuned-docvqa
\ No newline at end of file

From 37794943819c6c3d51e796611d3de630e7ba3a26 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:35:28 +0700
Subject: [PATCH 053/408] Add model
 2023-11-15-bert_qa_bert_l_squadv1.1_sl384_en

---
 ...11-15-bert_qa_bert_l_squadv1.1_sl384_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl384_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl384_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl384_en.md
new file mode 100644
index 00000000000000..54c679cb71dde9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_l_squadv1.1_sl384_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from vuiseng9)
+author: John Snow Labs
+name: bert_qa_bert_l_squadv1.1_sl384
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-l-squadv1.1-sl384` is a English model orginally trained by `vuiseng9`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_l_squadv1.1_sl384_en_5.2.0_3.0_1700062421907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_l_squadv1.1_sl384_en_5.2.0_3.0_1700062421907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_l_squadv1.1_sl384","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_l_squadv1.1_sl384","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.sl384.by_vuiseng9").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_l_squadv1.1_sl384|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/vuiseng9/bert-l-squadv1.1-sl384
\ No newline at end of file

From 0ccd4f70c0f8d5c09fa8cc9b8dbd85cf27f8fa3e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:37:42 +0700
Subject: [PATCH 054/408] Add model
 2023-11-15-bert_qa_beto_base_spanish_sqac_es

---
 ...11-15-bert_qa_beto_base_spanish_sqac_es.md | 112 ++++++++++++++++++
 1 file changed, 112 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_beto_base_spanish_sqac_es.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_beto_base_spanish_sqac_es.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_beto_base_spanish_sqac_es.md
new file mode 100644
index 00000000000000..7298a72104e6b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_beto_base_spanish_sqac_es.md
@@ -0,0 +1,112 @@
+---
+layout: model
+title: Spanish BertForQuestionAnswering model (from IIC)
+author: John Snow Labs
+name: bert_qa_beto_base_spanish_sqac
+date: 2023-11-15
+tags: [es, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `beto-base-spanish-sqac` is a Spanish model orginally trained by `IIC`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_beto_base_spanish_sqac_es_5.2.0_3.0_1700062655500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_beto_base_spanish_sqac_es_5.2.0_3.0_1700062655500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_beto_base_spanish_sqac","es") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_beto_base_spanish_sqac","es")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.answer_question.sqac.bert.base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_beto_base_spanish_sqac|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|es|
+|Size:|409.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/IIC/beto-base-spanish-sqac
+- https://paperswithcode.com/sota?task=question-answering&dataset=PlanTL-GOB-ES%2FSQAC
+- https://arxiv.org/abs/2107.07253
+- https://github.com/dccuchile/beto
+- https://www.bsc.es/
\ No newline at end of file

From eca9714ac093f3b0aafd7bba6c62a2fb4c159737 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:38:43 +0700
Subject: [PATCH 055/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en

---
 ...ew_shot_k_256_finetuned_squad_seed_8_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..91c2e223cd5436
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-8` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en_5.2.0_3.0_1700062697002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8_en_5.2.0_3.0_1700062697002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_8_base_256d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|383.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-8
\ No newline at end of file

From 88564920998110f95f923cf0ac13e08d755c269f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:40:16 +0700
Subject: [PATCH 056/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en

---
 ...d_whole_word_masking_finetuned_chaii_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en.md
new file mode 100644
index 00000000000000..5b6dc827f5da0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from SauravMaheshkar)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-whole-word-masking-finetuned-chaii` is a English model orginally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en_5.2.0_3.0_1700062797772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii_en_5.2.0_3.0_1700062797772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.bert.large_uncased_uncased_whole_word_masking_finetuned.by_SauravMaheshkar").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_whole_word_masking_finetuned_chaii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/bert-large-uncased-whole-word-masking-finetuned-chaii
\ No newline at end of file

From 6c8aaa4a43bbc887c7ea3983808f5b99ecea161a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:41:42 +0700
Subject: [PATCH 057/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en

---
 ...etuned_squad_finetuned_islamic_squad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en.md
new file mode 100644
index 00000000000000..40bbc9e1f22a0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from haddadalwi)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-islamic-squad` is a English model orginally trained by `haddadalwi`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en_5.2.0_3.0_1700062882246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad_en_5.2.0_3.0_1700062882246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.large_uncased.by_haddadalwi").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_islamic_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/haddadalwi/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-islamic-squad
\ No newline at end of file

From 137b018f9cf8e8c7b1445999a3a627d677e7949f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:43:07 +0700
Subject: [PATCH 058/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en

---
 ...ert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en.md
index 8bfe11974a0ca3..d905f075d07840 100644
--- a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en.md
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en.md
@@ -28,8 +28,8 @@ Pretrained Question Answering model, adapted from Hugging Face and curated to pr
 {:.btn-box}
 <button class="button button-orange" disabled>Live Demo</button>
 <button class="button button-orange" disabled>Open in Colab</button>
-[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en_5.2.0_3.0_1700015715389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
-[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en_5.2.0_3.0_1700015715389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en_5.2.0_3.0_1700062977896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en_5.2.0_3.0_1700062977896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
 
 ## How to use
 

From 8fbf4f55c6498fdab1b0caefb7c9afcae3441766 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:44:07 +0700
Subject: [PATCH 059/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en

---
 ...ew_shot_k_32_finetuned_squad_seed_10_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en.md
new file mode 100644
index 00000000000000..101322fb7ea94d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-10` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en_5.2.0_3.0_1700062985400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10_en_5.2.0_3.0_1700062985400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_32d_seed_10").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|376.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-10
\ No newline at end of file

From 216abc22f99666a299ebea9b1e477814de249878 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:45:07 +0700
Subject: [PATCH 060/408] Add model 2023-11-15-bert_qa_bert_large_faquad_en

---
 ...2023-11-15-bert_qa_bert_large_faquad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_faquad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_faquad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_faquad_en.md
new file mode 100644
index 00000000000000..16eae79e99df80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_faquad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from ricardo-filho)
+author: John Snow Labs
+name: bert_qa_bert_large_faquad
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_large_faquad` is a English model orginally trained by `ricardo-filho`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_faquad_en_5.2.0_3.0_1700062980803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_faquad_en_5.2.0_3.0_1700062980803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_faquad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_faquad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.large.by_ricardo-filho").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_faquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ricardo-filho/bert_large_faquad
\ No newline at end of file

From 6663307056cbff1cead7def8f0dcc3116e6e698d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:46:17 +0700
Subject: [PATCH 061/408] Add model
 2023-11-15-bert_qa_bert_multi_cased_finetuned_chaii_en

---
 ..._qa_bert_multi_cased_finetuned_chaii_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_chaii_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_chaii_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_chaii_en.md
new file mode 100644
index 00000000000000..c7c5e50fe633b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_chaii_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from SauravMaheshkar)
+author: John Snow Labs
+name: bert_qa_bert_multi_cased_finetuned_chaii
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-multi-cased-finetuned-chaii` is a English model orginally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_cased_finetuned_chaii_en_5.2.0_3.0_1700063164747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_cased_finetuned_chaii_en_5.2.0_3.0_1700063164747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_multi_cased_finetuned_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_multi_cased_finetuned_chaii","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.bert.cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_multi_cased_finetuned_chaii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/bert-multi-cased-finetuned-chaii
\ No newline at end of file

From 0a8e4666bdad0fc05c74b14ab1efc4079914347e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:47:38 +0700
Subject: [PATCH 062/408] Add model
 2023-11-15-bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx

---
 ..._cased_finedtuned_xquad_tydiqa_goldp_xx.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx.md
new file mode 100644
index 00000000000000..1ebde69b795a6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering model (from mrm8488)
+author: John Snow Labs
+name: bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp
+date: 2023-11-15
+tags: [te, en, open_source, question_answering, bert, xx, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-multi-cased-finedtuned-xquad-tydiqa-goldp` is a Multilingual model orginally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx_5.2.0_3.0_1700063247297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx_5.2.0_3.0_1700063247297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp","xx") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp","xx")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("xx.answer_question.xquad_tydiqa.bert.cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+-  https://huggingface.co/mrm8488/bert-multi-cased-finedtuned-xquad-tydiqa-goldp
\ No newline at end of file

From 31bc8d0cb9a20ab6024d6d1ce85f6b1176d3566e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:48:38 +0700
Subject: [PATCH 063/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en

---
 ...few_shot_k_32_finetuned_squad_seed_4_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..e43dd10e0eee1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-4` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en_5.2.0_3.0_1700063261261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4_en_5.2.0_3.0_1700063261261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_4_base_32d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|376.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-4
\ No newline at end of file

From 1287a6494535482f82a557f17d9f411076cf5846 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:49:39 +0700
Subject: [PATCH 064/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en

---
 ...few_shot_k_64_finetuned_squad_seed_0_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en.md
new file mode 100644
index 00000000000000..7faf2d485c372f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-0` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en_5.2.0_3.0_1700063265809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0_en_5.2.0_3.0_1700063265809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_64d_seed_0").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_0|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|378.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-0
\ No newline at end of file

From 0475f0887bdbed1e99a9dfad1fca2fa5cfd9b392 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:50:39 +0700
Subject: [PATCH 065/408] Add model
 2023-11-15-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en

---
 ..._l_10_h_512_a_8_cord19_200616_squad2_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en.md
new file mode 100644
index 00000000000000..8bb7953640551b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2 BertForQuestionAnswering from aodiniz
+author: John Snow Labs
+name: bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2` is a English model originally trained by aodiniz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en_5.2.0_3.0_1700063358643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en_5.2.0_3.0_1700063358643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|177.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/aodiniz/bert_uncased_L-10_H-512_A-8_cord19-200616_squad2
\ No newline at end of file

From 5273903de5d0d6fe158857d0291a2e11da620fa6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:52:00 +0700
Subject: [PATCH 066/408] Add model
 2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en

---
 ...whole_word_masking_finetuned_squadv2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..13c4d7d0defeae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from madlag)
+author: John Snow Labs
+name: bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-uncased-whole-word-masking-finetuned-squadv2` is a English model orginally trained by `madlag`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en_5.2.0_3.0_1700063498100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en_5.2.0_3.0_1700063498100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.large_uncased_whole_word_masking_v2.by_madlag").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/madlag/bert-large-uncased-whole-word-masking-finetuned-squadv2
\ No newline at end of file

From ae8c80538ce2877443f944559b1d1e7f11b8aae8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:53:00 +0700
Subject: [PATCH 067/408] Add model
 2023-11-15-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en

---
 ...d_l_4_h_512_a_8_cord19_200616_squad2_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en.md
new file mode 100644
index 00000000000000..9dace6c0e2dd6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2 BertForQuestionAnswering from aodiniz
+author: John Snow Labs
+name: bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2` is a English model originally trained by aodiniz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en_5.2.0_3.0_1700063519961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en_5.2.0_3.0_1700063519961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|106.9 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/aodiniz/bert_uncased_L-4_H-512_A-8_cord19-200616_squad2
\ No newline at end of file

From 9961fdce7cc2e95baaf79714b9ac2edfa7d5a9d5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:54:00 +0700
Subject: [PATCH 068/408] Add model
 2023-11-15-bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en

---
 ...etuned_xquadv1_finetuned_squad_colab_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en.md
new file mode 100644
index 00000000000000..0c281bcb536c3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from TingChenChang)
+author: John Snow Labs
+name: bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-multi-cased-finetuned-xquadv1-finetuned-squad-colab` is a English model orginally trained by `TingChenChang`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en_5.2.0_3.0_1700063606759.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en_5.2.0_3.0_1700063606759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.xquad_squad.bert.cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/TingChenChang/bert-multi-cased-finetuned-xquadv1-finetuned-squad-colab
\ No newline at end of file

From eb6510786e4f148f16ee581a8402710663e2d940 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:55:01 +0700
Subject: [PATCH 069/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en

---
 ...few_shot_k_32_finetuned_squad_seed_6_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..20b41039741d4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-6` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en_5.2.0_3.0_1700063566487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6_en_5.2.0_3.0_1700063566487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_32d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|376.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-6
\ No newline at end of file

From ae221a437e0ac875fd31f60e3139b92f10162949 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:56:01 +0700
Subject: [PATCH 070/408] Add model 2023-11-15-bert_qa_squad1.1_1_en

---
 .../2023-11-15-bert_qa_squad1.1_1_en.md       | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad1.1_1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad1.1_1_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad1.1_1_en.md
new file mode 100644
index 00000000000000..c0b4e0e815b33d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad1.1_1_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from maroo93)
+author: John Snow Labs
+name: bert_qa_squad1.1_1
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad1.1_1` is a English model orginally trained by `maroo93`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad1.1_1_en_5.2.0_3.0_1700063541554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad1.1_1_en_5.2.0_3.0_1700063541554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad1.1_1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_squad1.1_1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.v1.1.by_maroo93").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad1.1_1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/maroo93/squad1.1_1
\ No newline at end of file

From d3161a904c8fce658a9be17622f08b4906274712 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:57:20 +0700
Subject: [PATCH 071/408] Add model 2023-11-15-bert_qa_squad2.0_en

---
 .../2023-11-15-bert_qa_squad2.0_en.md         | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad2.0_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad2.0_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad2.0_en.md
new file mode 100644
index 00000000000000..77707368717cff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad2.0_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from maroo93)
+author: John Snow Labs
+name: bert_qa_squad2.0
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad2.0` is a English model orginally trained by `maroo93`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad2.0_en_5.2.0_3.0_1700063832186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad2.0_en_5.2.0_3.0_1700063832186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad2.0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_squad2.0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad2.0|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/maroo93/squad2.0
\ No newline at end of file

From b001dff7a72f5a9f5a28f5e612de39c0035f04c2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:58:21 +0700
Subject: [PATCH 072/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en

---
 ...few_shot_k_32_finetuned_squad_seed_8_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..f81ed18b47fb6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-8` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en_5.2.0_3.0_1700063835701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8_en_5.2.0_3.0_1700063835701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_8_base_32d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|376.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-8
\ No newline at end of file

From 39f7464664d5f569ba4df80a80412faf63befc96 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 22:59:21 +0700
Subject: [PATCH 073/408] Add model 2023-11-15-bert_qa_mqa_sim_en

---
 .../2023-11-15-bert_qa_mqa_sim_en.md          | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_sim_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_sim_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_sim_en.md
new file mode 100644
index 00000000000000..5c46c0a669c73f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_sim_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from xraychen)
+author: John Snow Labs
+name: bert_qa_mqa_sim
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mqa-sim` is a English model orginally trained by `xraychen`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_mqa_sim_en_5.2.0_3.0_1700063910561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_mqa_sim_en_5.2.0_3.0_1700063910561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_mqa_sim","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_mqa_sim","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.sim.by_xraychen").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_mqa_sim|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/xraychen/mqa-sim
\ No newline at end of file

From 2e827d19b143dd4a90760354c187e9505568da32 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:00:21 +0700
Subject: [PATCH 074/408] Add model 2023-11-15-bert_qa_roberta_wwm_ext_larg_zh

---
 ...3-11-15-bert_qa_roberta_wwm_ext_larg_zh.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_wwm_ext_larg_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_wwm_ext_larg_zh.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_wwm_ext_larg_zh.md
new file mode 100644
index 00000000000000..f052cd79a98507
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_wwm_ext_larg_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese BertForQuestionAnswering Cased model (from wskhanh)
+author: John Snow Labs
+name: bert_qa_roberta_wwm_ext_larg
+date: 2023-11-15
+tags: [zh, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `Roberta-wwm-ext-larg` is a Chinese model originally trained by `wskhanh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_wwm_ext_larg_zh_5.2.0_3.0_1700064001338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_wwm_ext_larg_zh_5.2.0_3.0_1700064001338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_roberta_wwm_ext_larg","zh")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_roberta_wwm_ext_larg","zh")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_roberta_wwm_ext_larg|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|zh|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/wskhanh/Roberta-wwm-ext-larg
\ No newline at end of file

From 4d11371ab5a8475509bdba9a9d2dbaf61d54d49d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:01:23 +0700
Subject: [PATCH 075/408] Add model
 2023-11-15-bert_qa_bertserini_bert_large_squad_en

---
 ...-bert_qa_bertserini_bert_large_squad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertserini_bert_large_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertserini_bert_large_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertserini_bert_large_squad_en.md
new file mode 100644
index 00000000000000..49a6e71f334a1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_bertserini_bert_large_squad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from rsvp-ai)
+author: John Snow Labs
+name: bert_qa_bertserini_bert_large_squad
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bertserini-bert-large-squad` is a English model orginally trained by `rsvp-ai`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_bertserini_bert_large_squad_en_5.2.0_3.0_1700064063590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_bertserini_bert_large_squad_en_5.2.0_3.0_1700064063590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_bertserini_bert_large_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_bertserini_bert_large_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.large.by_rsvp-ai").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_bertserini_bert_large_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/rsvp-ai/bertserini-bert-large-squad
\ No newline at end of file

From 1047aa844bb7c8d6d5e338039ddfb732dad9525d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:02:23 +0700
Subject: [PATCH 076/408] Add model
 2023-11-15-bert_qa_spasis_finetuned_squad_accelera_en

---
 ...t_qa_spasis_finetuned_squad_accelera_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spasis_finetuned_squad_accelera_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spasis_finetuned_squad_accelera_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spasis_finetuned_squad_accelera_en.md
new file mode 100644
index 00000000000000..c1aa7bdf347803
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spasis_finetuned_squad_accelera_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from spasis)
+author: John Snow Labs
+name: bert_qa_spasis_finetuned_squad_accelera
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad-accelerate` is a English model originally trained by `spasis`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spasis_finetuned_squad_accelera_en_5.2.0_3.0_1700064116229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spasis_finetuned_squad_accelera_en_5.2.0_3.0_1700064116229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spasis_finetuned_squad_accelera","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spasis_finetuned_squad_accelera","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.finetuned_accelera.by_spasis").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spasis_finetuned_squad_accelera|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/spasis/bert-finetuned-squad-accelerate
\ No newline at end of file

From 405a4333feaa90979f9b51d049912fb727ce2046 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:03:24 +0700
Subject: [PATCH 077/408] Add model 2023-11-15-bert_qa_mqa_unsupsim_en

---
 .../2023-11-15-bert_qa_mqa_unsupsim_en.md     | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_unsupsim_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_unsupsim_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_unsupsim_en.md
new file mode 100644
index 00000000000000..3249cd1ff6c3c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_mqa_unsupsim_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from xraychen)
+author: John Snow Labs
+name: bert_qa_mqa_unsupsim
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mqa-unsupsim` is a English model orginally trained by `xraychen`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_mqa_unsupsim_en_5.2.0_3.0_1700064165660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_mqa_unsupsim_en_5.2.0_3.0_1700064165660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_mqa_unsupsim","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_mqa_unsupsim","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.unsupsim.by_xraychen").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_mqa_unsupsim|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/xraychen/mqa-unsupsim
\ No newline at end of file

From f03bad7b401d1671d7d5e09f03e2b0ce1ee2d49a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:04:24 +0700
Subject: [PATCH 078/408] Add model 2023-11-15-bert_qa_squad_mbert_model_2_en

---
 ...23-11-15-bert_qa_squad_mbert_model_2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_mbert_model_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_mbert_model_2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_mbert_model_2_en.md
new file mode 100644
index 00000000000000..0f65f28da5bc27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_mbert_model_2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from ZYW)
+author: John Snow Labs
+name: bert_qa_squad_mbert_model_2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad-mbert-model_2` is a English model orginally trained by `ZYW`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_mbert_model_2_en_5.2.0_3.0_1700064192848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_mbert_model_2_en_5.2.0_3.0_1700064192848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad_mbert_model_2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_squad_mbert_model_2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.multi_lingual_bert.v2.by_ZYW").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad_mbert_model_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ZYW/squad-mbert-model_2
\ No newline at end of file

From 0e7fa41b42840d54a69da311aa209284a5135ba5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:06:10 +0700
Subject: [PATCH 079/408] Add model
 2023-11-15-bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en

---
 ...se_uncased_timestep_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..153c2b9aa3c555
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_bert-base-uncased_TIMESTEP_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700064358012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700064358012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_base_uncased_timestep_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_bert-base-uncased_TIMESTEP_squadv2_epochs_3
\ No newline at end of file

From 0739014641c248fc98978622f9647d585c6bd795 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:07:10 +0700
Subject: [PATCH 080/408] Add model 2023-11-15-bert_qa_squad_malay_bert_base_ms

---
 ...-11-15-bert_qa_squad_malay_bert_base_ms.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_malay_bert_base_ms.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_malay_bert_base_ms.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_malay_bert_base_ms.md
new file mode 100644
index 00000000000000..28df58e3169229
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_malay_bert_base_ms.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Malay (macrolanguage) bert_qa_squad_malay_bert_base BertForQuestionAnswering from zhufy
+author: John Snow Labs
+name: bert_qa_squad_malay_bert_base
+date: 2023-11-15
+tags: [bert, ms, open_source, question_answering, onnx]
+task: Question Answering
+language: ms
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_squad_malay_bert_base` is a Malay (macrolanguage) model originally trained by zhufy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_malay_bert_base_ms_5.2.0_3.0_1700064386332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_malay_bert_base_ms_5.2.0_3.0_1700064386332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad_malay_bert_base","ms") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_squad_malay_bert_base", "ms")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad_malay_bert_base|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ms|
+|Size:|412.1 MB|
+
+## References
+
+https://huggingface.co/zhufy/squad-ms-bert-base
\ No newline at end of file

From 1371097de85b99c0af3dbb7ba8eb1d21ac1c2059 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:08:11 +0700
Subject: [PATCH 081/408] Add model
 2023-11-15-bert_qa_squad_with_greetings_v2_en

---
 ...1-15-bert_qa_squad_with_greetings_v2_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_with_greetings_v2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_with_greetings_v2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_with_greetings_v2_en.md
new file mode 100644
index 00000000000000..81bba63735d9aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_with_greetings_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from moquanyi)
+author: John Snow Labs
+name: bert_qa_squad_with_greetings_v2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad_with_greetings-v2` is a English model originally trained by `moquanyi`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_with_greetings_v2_en_5.2.0_3.0_1700064472186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_with_greetings_v2_en_5.2.0_3.0_1700064472186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_squad_with_greetings_v2","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_squad_with_greetings_v2","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad_with_greetings_v2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/moquanyi/squad_with_greetings-v2
\ No newline at end of file

From ad66c800c7077b3f0af641909183fee63ed44e58 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:09:11 +0700
Subject: [PATCH 082/408] Add model
 2023-11-15-bert_qa_multilingual_bert_base_cased_hindi_hi

---
 ...a_multilingual_bert_base_cased_hindi_hi.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_multilingual_bert_base_cased_hindi_hi.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_multilingual_bert_base_cased_hindi_hi.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_multilingual_bert_base_cased_hindi_hi.md
new file mode 100644
index 00000000000000..3686f6c5c13814
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_multilingual_bert_base_cased_hindi_hi.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Hindi BertForQuestionAnswering model (from bhavikardeshna)
+author: John Snow Labs
+name: bert_qa_multilingual_bert_base_cased_hindi
+date: 2023-11-15
+tags: [open_source, question_answering, bert, hi, onnx]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `multilingual-bert-base-cased-hindi` is a Hindi model orginally trained by `bhavikardeshna`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_multilingual_bert_base_cased_hindi_hi_5.2.0_3.0_1700064514465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_multilingual_bert_base_cased_hindi_hi_5.2.0_3.0_1700064514465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_multilingual_bert_base_cased_hindi","hi") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_multilingual_bert_base_cased_hindi","hi")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("hi.answer_question.bert.multilingual_hindi_tuned_base_cased.by_bhavikardeshna").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_multilingual_bert_base_cased_hindi|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|hi|
+|Size:|665.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/bhavikardeshna/multilingual-bert-base-cased-hindi
\ No newline at end of file

From f8ff8ff158666cf3bb7913dd45e1999b2d65e7b4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:10:11 +0700
Subject: [PATCH 083/408] Add model 2023-11-15-bert_qa_sd3_en

---
 .../ahmedlone127/2023-11-15-bert_qa_sd3_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_en.md
new file mode 100644
index 00000000000000..16e6d47144c87f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from motiondew)
+author: John Snow Labs
+name: bert_qa_sd3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-sd3` is a English model originally trained by `motiondew`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sd3_en_5.2.0_3.0_1700064473704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sd3_en_5.2.0_3.0_1700064473704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sd3","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_sd3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.sd3.by_motiondew").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sd3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/motiondew/bert-sd3
\ No newline at end of file

From ea99d5d94b26aef1af0f9c86a38b75b913160d9b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:11:11 +0700
Subject: [PATCH 084/408] Add model
 2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en

---
 ...e_base_uncased_easy_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..02a9ebeda2880d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipe-bert-base-uncased_EASY_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en_5.2.0_3.0_1700064649328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3_en_5.2.0_3.0_1700064649328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_recipe_base_uncased_easy_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_recipe-bert-base-uncased_EASY_squadv2_epochs_3
\ No newline at end of file

From 0a6dc5fb775cdc4e153109dc1319acc4b1dcb121 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:12:11 +0700
Subject: [PATCH 085/408] Add model
 2023-11-15-bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en

---
 ...s_xtremedistil_l6_h256_uncased_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en.md
new file mode 100644
index 00000000000000..b603917c2957c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from SebOchs)
+author: John Snow Labs
+name: bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l6-h256-uncased-squad` is a English model originally trained by `SebOchs`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en_5.2.0_3.0_1700064675507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad_en_5.2.0_3.0_1700064675507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sebochs_xtremedistil_l6_h256_uncased_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|47.3 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SebOchs/xtremedistil-l6-h256-uncased-squad
\ No newline at end of file

From 523f70805db14f2599af8abee75b6ea0fd9d0580 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:13:12 +0700
Subject: [PATCH 086/408] Add model
 2023-11-15-bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en

---
 ...db_bert_base_uncased_finetuned_squad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..d229291c7202cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from srmukundb)
+author: John Snow Labs
+name: bert_qa_srmukundb_bert_base_uncased_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-finetuned-squad` is a English model orginally trained by `srmukundb`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700064675052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_srmukundb_bert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700064675052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_srmukundb_bert_base_uncased_finetuned_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_srmukundb_bert_base_uncased_finetuned_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.base_uncased.by_srmukundb").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_srmukundb_bert_base_uncased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/srmukundb/bert-base-uncased-finetuned-squad
\ No newline at end of file

From 92750c61d26f20cbd3edee14a964e1c529d68e19 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:14:12 +0700
Subject: [PATCH 087/408] Add model
 2023-11-15-bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en

---
 ...tilbert_base_uncased_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..a5731ad9a7f000
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from negfir)
+author: John Snow Labs
+name: bert_qa_negfir_distilbert_base_uncased_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `distilbert-base-uncased-finetuned-squad` is a English model originally trained by `negfir`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700064684620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_negfir_distilbert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700064684620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_negfir_distilbert_base_uncased_finetuned_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_negfir_distilbert_base_uncased_finetuned_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.distilled_uncased_base_finetuned").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_negfir_distilbert_base_uncased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|200.6 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/negfir/distilbert-base-uncased-finetuned-squad
\ No newline at end of file

From b81718efce79f4f82853dd24f9b08e677ce2bcc2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:15:12 +0700
Subject: [PATCH 088/408] Add model 2023-11-15-bert_qa_squad_xxl_cased_hub1_it

---
 ...3-11-15-bert_qa_squad_xxl_cased_hub1_it.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_xxl_cased_hub1_it.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_xxl_cased_hub1_it.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_xxl_cased_hub1_it.md
new file mode 100644
index 00000000000000..15698bbf859b31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_squad_xxl_cased_hub1_it.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: Italian BertForQuestionAnswering model (from luigisaetta)
+author: John Snow Labs
+name: bert_qa_squad_xxl_cased_hub1
+date: 2023-11-15
+tags: [it, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: it
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad_it_xxl_cased_hub1` is a Italian model originally trained by `luigisaetta`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_xxl_cased_hub1_it_5.2.0_3.0_1700064714351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_xxl_cased_hub1_it_5.2.0_3.0_1700064714351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad_xxl_cased_hub1","it") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Qual è il mio nome?", "Mi chiamo Clara e vivo a Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_squad_xxl_cased_hub1","it") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Qual è il mio nome?", "Mi chiamo Clara e vivo a Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("it.answer_question.squad.bert.xxl_cased").predict("""Qual è il mio nome?|||"Mi chiamo Clara e vivo a Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad_xxl_cased_hub1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|it|
+|Size:|412.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/luigisaetta/squad_it_xxl_cased_hub1
+- https://github.com/luigisaetta/nlp-qa-italian/blob/main/train_squad_it_final1.ipynb
\ No newline at end of file

From dde449bc89fbc7eeb8fefb0b0efdefcdfd721477 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:17:37 +0700
Subject: [PATCH 089/408] Add model
 2023-11-15-bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en

---
 ...a_set_date_1_lr_2e_5_bosnian_32_ep_3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en.md
new file mode 100644
index 00000000000000..14ffbe79b96edd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3 BertForQuestionAnswering from motiondew
+author: John Snow Labs
+name: bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3` is a English model originally trained by motiondew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700065047343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700065047343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_set_date_1_lr_2e_5_bosnian_32_ep_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/motiondew/bert-set_date_1-lr-2e-5-bs-32-ep-3
\ No newline at end of file

From 90f1db5c9b9ef348fd30e987dcd424bcce743470 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:28:48 +0700
Subject: [PATCH 090/408] Add model
 2023-11-15-bert_qa_ss756_base_cased_finetuned_squad_en

---
 ..._qa_ss756_base_cased_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_ss756_base_cased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_ss756_base_cased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_ss756_base_cased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..151d524175df10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_ss756_base_cased_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from ss756)
+author: John Snow Labs
+name: bert_qa_ss756_base_cased_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-cased-finetuned-squad` is a English model originally trained by `ss756`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_ss756_base_cased_finetuned_squad_en_5.2.0_3.0_1700065720292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_ss756_base_cased_finetuned_squad_en_5.2.0_3.0_1700065720292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ss756_base_cased_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ss756_base_cased_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_ss756_base_cased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ss756/bert-base-cased-finetuned-squad
\ No newline at end of file

From 0048d90e03f21ff58474fb7dc36c9a59f43c6355 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:31:17 +0700
Subject: [PATCH 091/408] Add model 2023-11-15-bert_qa_results_en

---
 .../2023-11-15-bert_qa_results_en.md          | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_results_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_results_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_results_en.md
new file mode 100644
index 00000000000000..95fba0909849a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_results_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from ericRosello)
+author: John Snow Labs
+name: bert_qa_results
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `results` is a English model orginally trained by `ericRosello`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_results_en_5.2.0_3.0_1700065867532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_results_en_5.2.0_3.0_1700065867532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_results","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_results","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.by_ericRosello").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_results|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ericRosello/results
\ No newline at end of file

From b1cb68d19a03470146f3d865db0eddffcadd72b3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:36:05 +0700
Subject: [PATCH 092/408] Add model 2023-11-15-bert_qa_srcoc_es

---
 .../2023-11-15-bert_qa_srcoc_es.md            | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_srcoc_es.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_srcoc_es.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_srcoc_es.md
new file mode 100644
index 00000000000000..ceddc0e1054f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_srcoc_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Spanish BertForQuestionAnswering Cased model (from srcocotero)
+author: John Snow Labs
+name: bert_qa_srcoc
+date: 2023-11-15
+tags: [es, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-qa-es` is a Spanish model originally trained by `srcocotero`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_srcoc_es_5.2.0_3.0_1700066156853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_srcoc_es_5.2.0_3.0_1700066156853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_srcoc","es")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_srcoc","es")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_srcoc|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|409.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/srcocotero/bert-qa-es
\ No newline at end of file

From 9e0e9c8c9ed76341d8e808ef0da6a280210ab426 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:39:23 +0700
Subject: [PATCH 093/408] Add model 2023-11-15-bert_qa_part_2_mbert_model_e1_en

---
 ...-11-15-bert_qa_part_2_mbert_model_e1_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_part_2_mbert_model_e1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_part_2_mbert_model_e1_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_part_2_mbert_model_e1_en.md
new file mode 100644
index 00000000000000..df176bbadb1657
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_part_2_mbert_model_e1_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from horsbug98)
+author: John Snow Labs
+name: bert_qa_part_2_mbert_model_e1
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `Part_2_mBERT_Model_E1` is a English model originally trained by `horsbug98`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_part_2_mbert_model_e1_en_5.2.0_3.0_1700066351101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_part_2_mbert_model_e1_en_5.2.0_3.0_1700066351101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_part_2_mbert_model_e1","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_part_2_mbert_model_e1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.tydiqa.").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_part_2_mbert_model_e1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/horsbug98/Part_2_mBERT_Model_E1
\ No newline at end of file

From e3ba954412efc36440b493df8899c802afa30e6c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:53:33 +0700
Subject: [PATCH 094/408] Add model
 2023-11-15-bert_qa_shash2409_finetuned_squad_en

---
 ...15-bert_qa_shash2409_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_shash2409_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shash2409_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shash2409_finetuned_squad_en.md
new file mode 100644
index 00000000000000..88a8f51ad957d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shash2409_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from shash2409)
+author: John Snow Labs
+name: bert_qa_shash2409_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `shash2409`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_shash2409_finetuned_squad_en_5.2.0_3.0_1700067204546.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_shash2409_finetuned_squad_en_5.2.0_3.0_1700067204546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shash2409_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shash2409_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_shash2409_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/shash2409/bert-finetuned-squad
\ No newline at end of file

From f362e875bfe084506c7503d2394c57922c29837e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Wed, 15 Nov 2023 23:57:10 +0700
Subject: [PATCH 095/408] Add model 2023-11-15-bert_qa_roberta_base_squad2_en

---
 ...23-11-15-bert_qa_roberta_base_squad2_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_squad2_en.md
new file mode 100644
index 00000000000000..8c58e97cca2b10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_squad2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from vvincentt)
+author: John Snow Labs
+name: bert_qa_roberta_base_squad2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad2` is a English model originally trained by `vvincentt`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_squad2_en_5.2.0_3.0_1700067423627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_squad2_en_5.2.0_3.0_1700067423627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_roberta_base_squad2","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_roberta_base_squad2","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_roberta_base_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/vvincentt/roberta-base-squad2
\ No newline at end of file

From a8fc4fa8488f3072d34673069b28f2398be88f06 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:01:15 +0700
Subject: [PATCH 096/408] Add model 2023-11-15-bert_qa_telugu_bertu_tydiqa_xx

---
 ...23-11-15-bert_qa_telugu_bertu_tydiqa_xx.md | 109 ++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_telugu_bertu_tydiqa_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_telugu_bertu_tydiqa_xx.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_telugu_bertu_tydiqa_xx.md
new file mode 100644
index 00000000000000..3cda2c55821709
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_telugu_bertu_tydiqa_xx.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering model (from kuppuluri)
+author: John Snow Labs
+name: bert_qa_telugu_bertu_tydiqa
+date: 2023-11-15
+tags: [te, en, open_source, question_answering, bert, xx, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `telugu_bertu_tydiqa` is a Multilingual model orginally trained by `kuppuluri`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_telugu_bertu_tydiqa_xx_5.2.0_3.0_1700067667402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_telugu_bertu_tydiqa_xx_5.2.0_3.0_1700067667402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_telugu_bertu_tydiqa","xx") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_telugu_bertu_tydiqa","xx")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("xx.answer_question.tydiqa.bert").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_telugu_bertu_tydiqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|412.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/kuppuluri/telugu_bertu_tydiqa
+- https://github.com/google-research-datasets/tydiqa
\ No newline at end of file

From d5807c08b4ec9fd5cad34085a342664d20e9ae58 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:10:41 +0700
Subject: [PATCH 097/408] Add model
 2023-11-15-bert_qa_susghosh_finetuned_squad_en

---
 ...-15-bert_qa_susghosh_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_susghosh_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_susghosh_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_susghosh_finetuned_squad_en.md
new file mode 100644
index 00000000000000..aabf15320c04a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_susghosh_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from susghosh)
+author: John Snow Labs
+name: bert_qa_susghosh_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `susghosh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_susghosh_finetuned_squad_en_5.2.0_3.0_1700068229977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_susghosh_finetuned_squad_en_5.2.0_3.0_1700068229977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_susghosh_finetuned_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_susghosh_finetuned_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.finetuned.by_susghosh").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_susghosh_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/susghosh/bert-finetuned-squad
\ No newline at end of file

From e5c28d4c7b78e6130e286057bb5865b0f0708da1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:11:41 +0700
Subject: [PATCH 098/408] Add model
 2023-11-15-bert_qa_question_answering_chinese_voidful_zh

---
 ...a_question_answering_chinese_voidful_zh.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_question_answering_chinese_voidful_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_question_answering_chinese_voidful_zh.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_question_answering_chinese_voidful_zh.md
new file mode 100644
index 00000000000000..bc03919db0c88e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_question_answering_chinese_voidful_zh.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Chinese bert_qa_question_answering_chinese_voidful BertForQuestionAnswering from voidful
+author: John Snow Labs
+name: bert_qa_question_answering_chinese_voidful
+date: 2023-11-15
+tags: [bert, zh, open_source, question_answering, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_question_answering_chinese_voidful` is a Chinese model originally trained by voidful.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_question_answering_chinese_voidful_zh_5.2.0_3.0_1700068229745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_question_answering_chinese_voidful_zh_5.2.0_3.0_1700068229745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_question_answering_chinese_voidful","zh") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_question_answering_chinese_voidful", "zh")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_question_answering_chinese_voidful|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|zh|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/voidful/question-answering-zh
\ No newline at end of file

From d154c24d98b2a61a37c0e0a5e06d80d9c9aaa4e0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:22:17 +0700
Subject: [PATCH 099/408] Add model
 2023-11-15-bert_qa_shawon100_finetuned_squad_en

---
 ...15-bert_qa_shawon100_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_shawon100_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shawon100_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shawon100_finetuned_squad_en.md
new file mode 100644
index 00000000000000..4a833b226d036b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shawon100_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from shawon100)
+author: John Snow Labs
+name: bert_qa_shawon100_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `shawon100`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_shawon100_finetuned_squad_en_5.2.0_3.0_1700068925335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_shawon100_finetuned_squad_en_5.2.0_3.0_1700068925335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shawon100_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shawon100_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_shawon100_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/shawon100/bert-finetuned-squad
\ No newline at end of file

From 5f78117ec86746438c88d446d0817c4fc23ffb02 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:23:17 +0700
Subject: [PATCH 100/408] Add model 2023-11-15-bert_qa_scibert_coqa_en

---
 .../2023-11-15-bert_qa_scibert_coqa_en.md     | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_scibert_coqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_scibert_coqa_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_scibert_coqa_en.md
new file mode 100644
index 00000000000000..9548415ee3bc67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_scibert_coqa_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from peggyhuang)
+author: John Snow Labs
+name: bert_qa_scibert_coqa
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `SciBERT-CoQA` is a English model originally trained by `peggyhuang`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_scibert_coqa_en_5.2.0_3.0_1700068925491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_scibert_coqa_en_5.2.0_3.0_1700068925491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_scibert_coqa","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_scibert_coqa","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.scibert.scibert.").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_scibert_coqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/peggyhuang/SciBERT-CoQA
\ No newline at end of file

From a689b6d42bbbfc3658606491c64650a25a49aa03 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:34:33 +0700
Subject: [PATCH 101/408] Add model
 2023-11-15-bert_qa_tinybert_6l_768d_squad2_en

---
 ...1-15-bert_qa_tinybert_6l_768d_squad2_en.md | 119 ++++++++++++++++++
 1 file changed, 119 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_en.md
new file mode 100644
index 00000000000000..b6b5e5df90a52e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_en.md
@@ -0,0 +1,119 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from deepset)
+author: John Snow Labs
+name: bert_qa_tinybert_6l_768d_squad2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tinybert-6l-768d-squad2` is a English model orginally trained by `deepset`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_en_5.2.0_3.0_1700069667496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_en_5.2.0_3.0_1700069667496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_tinybert_6l_768d_squad2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.tiny_768d").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tinybert_6l_768d_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|248.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/tinybert-6l-768d-squad2
+- https://github.com/deepset-ai/haystack/discussions
+- https://deepset.ai
+- https://twitter.com/deepset_ai
+- http://www.deepset.ai/jobs
+- https://haystack.deepset.ai/community/join
+- https://github.com/deepset-ai/haystack/
+- https://deepset.ai/german-bert
+- https://www.linkedin.com/company/deepset-ai/
+- https://arxiv.org/pdf/1909.10351.pdf
+- https://github.com/deepset-ai/FARM
+- https://deepset.ai/germanquad
\ No newline at end of file

From 6f1d10a63cf89bd178ef1a2e0e19474789297108 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:39:20 +0700
Subject: [PATCH 102/408] Add model 2023-11-15-bert_qa_questionansweing_en

---
 .../2023-11-15-bert_qa_questionansweing_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_questionansweing_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_questionansweing_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_questionansweing_en.md
new file mode 100644
index 00000000000000..2f5dd17a520102
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_questionansweing_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from ponmari)
+author: John Snow Labs
+name: bert_qa_questionansweing
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `QuestionAnsweingBert` is a English model originally trained by `ponmari`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_questionansweing_en_5.2.0_3.0_1700069952307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_questionansweing_en_5.2.0_3.0_1700069952307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_questionansweing","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_questionansweing","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.by_ponmari").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_questionansweing|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ponmari/QuestionAnsweingBert
\ No newline at end of file

From f64ed2180ac86421c8306a6a52621678a8b7689b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:54:07 +0700
Subject: [PATCH 103/408] Add model 2023-11-15-bert_qa_sd1_en

---
 .../ahmedlone127/2023-11-15-bert_qa_sd1_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd1_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd1_en.md
new file mode 100644
index 00000000000000..d068feb6363ee8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd1_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from motiondew)
+author: John Snow Labs
+name: bert_qa_sd1
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-sd1` is a English model originally trained by `motiondew`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sd1_en_5.2.0_3.0_1700070839724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sd1_en_5.2.0_3.0_1700070839724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sd1","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_sd1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.sd1.by_motiondew").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sd1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/motiondew/bert-sd1
\ No newline at end of file

From c95fd0028a981460e3a822feb5fd701e58ba17fa Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 00:58:31 +0700
Subject: [PATCH 104/408] Add model
 2023-11-15-bert_qa_tinybert_6l_768d_squad2_large_teach_en

---
 ..._tinybert_6l_768d_squad2_large_teach_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_large_teach_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_large_teach_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_large_teach_en.md
new file mode 100644
index 00000000000000..41db7b2d072647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_6l_768d_squad2_large_teach_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny Cased model (from MichelBartels)
+author: John Snow Labs
+name: bert_qa_tinybert_6l_768d_squad2_large_teach
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tinybert-6l-768d-squad2-large-teacher` is a English model originally trained by `MichelBartels`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teach_en_5.2.0_3.0_1700071106122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teach_en_5.2.0_3.0_1700071106122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teach","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teach","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2.large_tiny_768d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tinybert_6l_768d_squad2_large_teach|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|249.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/MichelBartels/tinybert-6l-768d-squad2-large-teacher
\ No newline at end of file

From 63ce8f3765f89117da6645466fafcdc0a26a2771 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:02:02 +0700
Subject: [PATCH 105/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en

---
 ...w_shot_k_1024_finetuned_squad_seed_0_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en.md
new file mode 100644
index 00000000000000..e89e15f3cc03d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-0` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en_5.2.0_3.0_1700071314719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0_en_5.2.0_3.0_1700071314719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_1024d_seed_0").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_0|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|389.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-0
\ No newline at end of file

From 50883f1f47d5f6c0448c6ce389df3c3fe9a9c0aa Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:08:37 +0700
Subject: [PATCH 106/408] Add model
 2023-11-15-bert_qa_ramrajput_finetuned_squad_en

---
 ...15-bert_qa_ramrajput_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_ramrajput_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_ramrajput_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_ramrajput_finetuned_squad_en.md
new file mode 100644
index 00000000000000..1ccddc27182c6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_ramrajput_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from ramrajput)
+author: John Snow Labs
+name: bert_qa_ramrajput_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `ramrajput`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_ramrajput_finetuned_squad_en_5.2.0_3.0_1700071709869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_ramrajput_finetuned_squad_en_5.2.0_3.0_1700071709869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ramrajput_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ramrajput_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_ramrajput_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ramrajput/bert-finetuned-squad
\ No newline at end of file

From 0ee37b1f35da8b8ffd1773a8b412eb474cd92ef1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:11:18 +0700
Subject: [PATCH 107/408] Add model 2023-11-15-bert_qa_test01_en

---
 .../2023-11-15-bert_qa_test01_en.md           | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_test01_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_test01_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_test01_en.md
new file mode 100644
index 00000000000000..4e9aed238da1d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_test01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from Akert)
+author: John Snow Labs
+name: bert_qa_test01
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `test01` is a English model originally trained by `Akert`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_test01_en_5.2.0_3.0_1700071870324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_test01_en_5.2.0_3.0_1700071870324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_test01","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_test01","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_test01|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Akert/test01
\ No newline at end of file

From 7c6f71d12409b01e7cfd2c5986368f1561cd26ec Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:13:28 +0700
Subject: [PATCH 108/408] Add model
 2023-11-15-bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en

---
 ...5-bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en.md
new file mode 100644
index 00000000000000..18dd38c31c7fff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_sd2_lr_5e_5_bosnian_32_e_3 BertForQuestionAnswering from motiondew
+author: John Snow Labs
+name: bert_qa_sd2_lr_5e_5_bosnian_32_e_3
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_sd2_lr_5e_5_bosnian_32_e_3` is a English model originally trained by motiondew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en_5.2.0_3.0_1700072001043.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sd2_lr_5e_5_bosnian_32_e_3_en_5.2.0_3.0_1700072001043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sd2_lr_5e_5_bosnian_32_e_3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_sd2_lr_5e_5_bosnian_32_e_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sd2_lr_5e_5_bosnian_32_e_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/motiondew/bert-sd2-lr-5e-5-bs-32-e-3
\ No newline at end of file

From e0328fba36b9d35b174bbaa7d50f9ac594f53f8c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:25:31 +0700
Subject: [PATCH 109/408] Add model
 2023-11-15-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en

---
 ...d_l_6_h_128_a_2_cord19_200616_squad2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en.md
new file mode 100644
index 00000000000000..630075e8dc7d4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-6_H-128_A-2_cord19-200616_squad2` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en_5.2.0_3.0_1700072728267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_en_5.2.0_3.0_1700072728267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2_cord19.uncased_6l_128d_a2a_128d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|19.6 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-6_H-128_A-2_cord19-200616_squad2
\ No newline at end of file

From d2e6e5955944ecc13bd2cc58eb1a383a93434734 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:26:31 +0700
Subject: [PATCH 110/408] Add model
 2023-11-15-bert_qa_tiny_wrslb_finetuned_squadv1_en

---
 ...bert_qa_tiny_wrslb_finetuned_squadv1_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_tiny_wrslb_finetuned_squadv1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tiny_wrslb_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tiny_wrslb_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..eb2d623050fbc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tiny_wrslb_finetuned_squadv1_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny model (from mrm8488)
+author: John Snow Labs
+name: bert_qa_tiny_wrslb_finetuned_squadv1
+date: 2023-11-15
+tags: [open_source, bert, question_answering, tiny, en, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BERT Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-tiny-wrslb-finetuned-squadv1` is a English model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_wrslb_finetuned_squadv1_en_5.2.0_3.0_1700072728247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_wrslb_finetuned_squadv1_en_5.2.0_3.0_1700072728247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tiny_wrslb_finetuned_squadv1","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["PUT YOUR 'QUESTION' STRING HERE?", "PUT YOUR 'CONTEXT' STRING HERE"]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_tiny_wrslb_finetuned_squadv1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("PUT YOUR 'QUESTION' STRING HERE?", "PUT YOUR 'CONTEXT' STRING HERE").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.tiny_finetuned").predict("""PUT YOUR 'QUESTION' STRING HERE?|||"PUT YOUR 'CONTEXT' STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tiny_wrslb_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+https://huggingface.co/mrm8488/bert-tiny-wrslb-finetuned-squadv1
\ No newline at end of file

From 09a8948daa7cbab9b78a6f17baa7c7c6120e1b5b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:28:35 +0700
Subject: [PATCH 111/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en

---
 ...w_shot_k_1024_finetuned_squad_seed_8_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..b4d07993c2a183
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-8` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en_5.2.0_3.0_1700072907682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8_en_5.2.0_3.0_1700072907682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_1024d_seed_8").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|390.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-8
\ No newline at end of file

From ccac416581dd3dd36d63e0f0f4af1a24cd4e8a1f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:34:19 +0700
Subject: [PATCH 112/408] Add model
 2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en

---
 ...t_base_uncased_easy_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..26f934efee8a2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_bert-base-uncased_EASY_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en_5.2.0_3.0_1700073251310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3_en_5.2.0_3.0_1700073251310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_base_uncased_easy_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_bert-base-uncased_EASY_squadv2_epochs_3
\ No newline at end of file

From 898f49138efdfc9ec3d3c1eca62a3d5489a2a122 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 01:43:16 +0700
Subject: [PATCH 113/408] Add model 2023-11-15-bert_qa_sd3_small_en

---
 .../2023-11-15-bert_qa_sd3_small_en.md        | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_small_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_small_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_small_en.md
new file mode 100644
index 00000000000000..8401bbddd0955c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sd3_small_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Small Cased model (from motiondew)
+author: John Snow Labs
+name: bert_qa_sd3_small
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-sd3-small` is a English model originally trained by `motiondew`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sd3_small_en_5.2.0_3.0_1700073781848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sd3_small_en_5.2.0_3.0_1700073781848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sd3_small","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_sd3_small","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.small.sd3_small.by_motiondew").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sd3_small|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/motiondew/bert-sd3-small
\ No newline at end of file

From 6d75f8b1b5906bc651a80ff49eb60ca6480f65f8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:03:38 +0700
Subject: [PATCH 114/408] Add model
 2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en

---
 ...cased_easy_timestep_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..0fb1355d455417
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_bert-base-uncased_EASY_TIMESTEP_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700075008869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700075008869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_base_uncased_easy_timestep_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_bert-base-uncased_EASY_TIMESTEP_squadv2_epochs_3
\ No newline at end of file

From ddd8257437da69b48c20892deb7302e307453869 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:06:54 +0700
Subject: [PATCH 115/408] Add model
 2023-11-15-bert_qa_sebastians_finetuned_squad_en

---
 ...5-bert_qa_sebastians_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebastians_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebastians_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebastians_finetuned_squad_en.md
new file mode 100644
index 00000000000000..40c22175bccbee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_sebastians_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from SebastianS)
+author: John Snow Labs
+name: bert_qa_sebastians_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `SebastianS`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sebastians_finetuned_squad_en_5.2.0_3.0_1700075206741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sebastians_finetuned_squad_en_5.2.0_3.0_1700075206741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sebastians_finetuned_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_sebastians_finetuned_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.finetuned_squad.by_SebastianS").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sebastians_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SebastianS/bert-finetuned-squad
\ No newline at end of file

From a15d94065023e74a517d493aed20d80b7cfd7ea2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:23:04 +0700
Subject: [PATCH 116/408] Add model
 2023-11-15-bert_qa_tinybert_general_4l_312d_squad_en

---
 ...rt_qa_tinybert_general_4l_312d_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_general_4l_312d_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_general_4l_312d_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_general_4l_312d_squad_en.md
new file mode 100644
index 00000000000000..67b083d08a321e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_tinybert_general_4l_312d_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny Cased model (from haritzpuerto)
+author: John Snow Labs
+name: bert_qa_tinybert_general_4l_312d_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `TinyBERT_General_4L_312D-squad` is a English model originally trained by `haritzpuerto`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_general_4l_312d_squad_en_5.2.0_3.0_1700076181489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_general_4l_312d_squad_en_5.2.0_3.0_1700076181489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tinybert_general_4l_312d_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_tinybert_general_4l_312d_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.tiny").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tinybert_general_4l_312d_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|53.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/haritzpuerto/TinyBERT_General_4L_312D-squad
\ No newline at end of file

From 7437b6fc76b0271bc09e44762d1fddf302289841 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:31:31 +0700
Subject: [PATCH 117/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en

---
 ...ew_shot_k_256_finetuned_squad_seed_2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..9447050c59f83e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-2` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en_5.2.0_3.0_1700076683284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2_en_5.2.0_3.0_1700076683284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_2_base_256d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|383.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-2
\ No newline at end of file

From 280d8e57faa80567d288db380986eb153af1e9ce Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:32:31 +0700
Subject: [PATCH 118/408] Add model
 2023-11-15-bert_qa_vedants01_finetuned_squad_en

---
 ...15-bert_qa_vedants01_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_vedants01_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_vedants01_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_vedants01_finetuned_squad_en.md
new file mode 100644
index 00000000000000..261a98ac738f02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_vedants01_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from VedantS01)
+author: John Snow Labs
+name: bert_qa_vedants01_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `VedantS01`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_vedants01_finetuned_squad_en_5.2.0_3.0_1700076702685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_vedants01_finetuned_squad_en_5.2.0_3.0_1700076702685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_vedants01_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_vedants01_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_vedants01_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/VedantS01/bert-finetuned-squad
\ No newline at end of file

From 3a5439288a7d24a08dc6af09a17e30c489d149d4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:33:31 +0700
Subject: [PATCH 119/408] Add model
 2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en

---
 ...cased_easy_timestep_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..fa2ad3c9139078
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipe-bert-base-uncased_EASY_TIMESTEP_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700076702862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700076702862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_recipe_base_uncased_easy_timestep_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_recipe-bert-base-uncased_EASY_TIMESTEP_squadv2_epochs_3
\ No newline at end of file

From dd786679013de863c1d14ceecc6120a80a8008d7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 02:35:57 +0700
Subject: [PATCH 120/408] Add model 2023-11-15-bert_qa_set_date_1_impartit_4_en

---
 ...-11-15-bert_qa_set_date_1_impartit_4_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_impartit_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_impartit_4_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_impartit_4_en.md
new file mode 100644
index 00000000000000..e9a182306be748
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_1_impartit_4_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from motiondew)
+author: John Snow Labs
+name: bert_qa_set_date_1_impartit_4
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `set_date_1-impartit_4-bert` is a English model originally trained by `motiondew`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_1_impartit_4_en_5.2.0_3.0_1700076947046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_1_impartit_4_en_5.2.0_3.0_1700076947046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_set_date_1_impartit_4","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_set_date_1_impartit_4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.set_date_1_impartit_4.by_motiondew").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_set_date_1_impartit_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/motiondew/set_date_1-impartit_4-bert
\ No newline at end of file

From 0b15d0cef8333e46e23e5a8f3c297beb05ac9b1c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:00:14 +0700
Subject: [PATCH 121/408] Add model
 2023-11-15-bert_qa_victorlee071200_base_cased_finetuned_squad_en

---
 ...lee071200_base_cased_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_victorlee071200_base_cased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_victorlee071200_base_cased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_victorlee071200_base_cased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..58f63c17171044
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_victorlee071200_base_cased_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from victorlee071200)
+author: John Snow Labs
+name: bert_qa_victorlee071200_base_cased_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-cased-finetuned-squad` is a English model originally trained by `victorlee071200`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_victorlee071200_base_cased_finetuned_squad_en_5.2.0_3.0_1700078403143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_victorlee071200_base_cased_finetuned_squad_en_5.2.0_3.0_1700078403143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_victorlee071200_base_cased_finetuned_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_victorlee071200_base_cased_finetuned_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.cased_base_finetuned.by_victorlee071200").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_victorlee071200_base_cased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/victorlee071200/bert-base-cased-finetuned-squad
\ No newline at end of file

From 8175ef0a263b8d39f9c80bd02309ec17733f796c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:02:34 +0700
Subject: [PATCH 122/408] Add model
 2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en

---
 ...recipe_base_uncased_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..878a4f7a9f8ac8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipe-bert-base-uncased_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en_5.2.0_3.0_1700078543892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3_en_5.2.0_3.0_1700078543892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_recipe_base_uncased_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_recipe-bert-base-uncased_squadv2_epochs_3
\ No newline at end of file

From 0374853aad1cfc4266674205eb32ac69bcad889d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:03:34 +0700
Subject: [PATCH 123/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en

---
 ...ew_shot_k_256_finetuned_squad_seed_6_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..72eaa932f0c9f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-6` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en_5.2.0_3.0_1700078543838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6_en_5.2.0_3.0_1700078543838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_6_base_256d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|383.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-6
\ No newline at end of file

From 1f279d73661e04ec7cab0bdc996f32496b615df1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:04:35 +0700
Subject: [PATCH 124/408] Add model
 2023-11-15-bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en

---
 ...a_set_date_2_lr_2e_5_bosnian_32_ep_3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en.md
new file mode 100644
index 00000000000000..1c238243e93959
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3 BertForQuestionAnswering from motiondew
+author: John Snow Labs
+name: bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3` is a English model originally trained by motiondew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700078543680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700078543680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/motiondew/bert-set_date_2-lr-2e-5-bs-32-ep-3
\ No newline at end of file

From 6fe7af7915cedd5c80107cf40765831076ec9f07 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:27:44 +0700
Subject: [PATCH 125/408] Add model
 2023-11-15-bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en

---
 ...a_set_date_2_lr_3e_5_bosnian_32_ep_3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en.md
new file mode 100644
index 00000000000000..97fd39ed127ec0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3 BertForQuestionAnswering from motiondew
+author: John Snow Labs
+name: bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3` is a English model originally trained by motiondew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700080056206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700080056206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_set_date_2_lr_3e_5_bosnian_32_ep_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/motiondew/bert-set_date_2-lr-3e-5-bs-32-ep-3
\ No newline at end of file

From 844768b589446aabb6a50cd9515da06f1a41be42 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:34:20 +0700
Subject: [PATCH 126/408] Add model
 2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en

---
 ...se_uncased_timestep_squadv2_epochs_3_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en.md
new file mode 100644
index 00000000000000..bb3085a0f074bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Uncased model (from AnonymousSub)
+author: John Snow Labs
+name: bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `recipe_triplet_recipe-bert-base-uncased_TIMESTEP_squadv2_epochs_3` is a English model originally trained by `AnonymousSub`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700080450858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3_en_5.2.0_3.0_1700080450858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_recipe_triplet_recipe_base_uncased_timestep_squadv2_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/recipe_triplet_recipe-bert-base-uncased_TIMESTEP_squadv2_epochs_3
\ No newline at end of file

From 5feab33acab396bc27970877f354299dc0ec508c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:53:54 +0700
Subject: [PATCH 127/408] Add model
 2023-11-15-bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en

---
 ...a_set_date_3_lr_2e_5_bosnian_32_ep_4_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en.md
new file mode 100644
index 00000000000000..869826b85f1cc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4 BertForQuestionAnswering from motiondew
+author: John Snow Labs
+name: bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4` is a English model originally trained by motiondew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en_5.2.0_3.0_1700081626662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4_en_5.2.0_3.0_1700081626662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/motiondew/bert-set_date_3-lr-2e-5-bs-32-ep-4
\ No newline at end of file

From c5e25a96bcfac45c827f316665ec9f182abb85f4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 03:58:13 +0700
Subject: [PATCH 128/408] Add model
 2023-11-15-bert_qa_reza_aditya_finetuned_squad_en

---
 ...-bert_qa_reza_aditya_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_reza_aditya_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_reza_aditya_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_reza_aditya_finetuned_squad_en.md
new file mode 100644
index 00000000000000..37e4c80cce9ebe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_reza_aditya_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from reza-aditya)
+author: John Snow Labs
+name: bert_qa_reza_aditya_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `reza-aditya`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_reza_aditya_finetuned_squad_en_5.2.0_3.0_1700081885655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_reza_aditya_finetuned_squad_en_5.2.0_3.0_1700081885655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_reza_aditya_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_reza_aditya_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_reza_aditya_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/reza-aditya/bert-finetuned-squad
\ No newline at end of file

From e0853078890ac3e3207db4c2e867e2c860296f68 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:00:19 +0700
Subject: [PATCH 129/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en

---
 ...ew_shot_k_512_finetuned_squad_seed_2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..969859c4ad93e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-2` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en_5.2.0_3.0_1700082007492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2_en_5.2.0_3.0_1700082007492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_2_base_512d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|386.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-2
\ No newline at end of file

From 714e2867a6fe495f7381e13798ff307b3a3e7ee4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:01:49 +0700
Subject: [PATCH 130/408] Add model
 2023-11-15-bert_qa_xdistil_l12_h384_squad2_en

---
 ...1-15-bert_qa_xdistil_l12_h384_squad2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_xdistil_l12_h384_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_xdistil_l12_h384_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_xdistil_l12_h384_squad2_en.md
new file mode 100644
index 00000000000000..dfb92631d34612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_xdistil_l12_h384_squad2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from nbroad)
+author: John Snow Labs
+name: bert_qa_xdistil_l12_h384_squad2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xdistil-l12-h384-squad2` is a English model orginally trained by `nbroad`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xdistil_l12_h384_squad2_en_5.2.0_3.0_1700082106520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xdistil_l12_h384_squad2_en_5.2.0_3.0_1700082106520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xdistil_l12_h384_squad2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_xdistil_l12_h384_squad2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.distilled").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xdistil_l12_h384_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|123.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/nbroad/xdistil-l12-h384-squad2
\ No newline at end of file

From 5dc6bdccb61f038f272195b6e922a8dc6fe3d7dd Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:02:49 +0700
Subject: [PATCH 131/408] Add model
 2023-11-15-electra_qa_biom_base_squad2_bioasq8b_en

---
 ...electra_qa_biom_base_squad2_bioasq8b_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-electra_qa_biom_base_squad2_bioasq8b_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-electra_qa_biom_base_squad2_bioasq8b_en.md b/docs/_posts/ahmedlone127/2023-11-15-electra_qa_biom_base_squad2_bioasq8b_en.md
new file mode 100644
index 00000000000000..c828219745a30a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-electra_qa_biom_base_squad2_bioasq8b_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English electra_qa_biom_base_squad2_bioasq8b BertForQuestionAnswering from sultan
+author: John Snow Labs
+name: electra_qa_biom_base_squad2_bioasq8b
+date: 2023-11-15
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_biom_base_squad2_bioasq8b` is a English model originally trained by sultan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_biom_base_squad2_bioasq8b_en_5.2.0_3.0_1700082106995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_biom_base_squad2_bioasq8b_en_5.2.0_3.0_1700082106995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_biom_base_squad2_bioasq8b","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_biom_base_squad2_bioasq8b", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_biom_base_squad2_bioasq8b|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/sultan/BioM-ELECTRA-Base-SQuAD2-BioASQ8B
\ No newline at end of file

From 88dff3ead6b0d05883a384678711c2b9f07f0e03 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:24:44 +0700
Subject: [PATCH 132/408] Add model
 2023-11-15-bert_qa_shadowtwin41_finetuned_squad_accelerate_en

---
 ...dowtwin41_finetuned_squad_accelerate_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_shadowtwin41_finetuned_squad_accelerate_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shadowtwin41_finetuned_squad_accelerate_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shadowtwin41_finetuned_squad_accelerate_en.md
new file mode 100644
index 00000000000000..90d99fbba418b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shadowtwin41_finetuned_squad_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from ShadowTwin41)
+author: John Snow Labs
+name: bert_qa_shadowtwin41_finetuned_squad_accelerate
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad-accelerate` is a English model originally trained by `ShadowTwin41`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_shadowtwin41_finetuned_squad_accelerate_en_5.2.0_3.0_1700083476522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_shadowtwin41_finetuned_squad_accelerate_en_5.2.0_3.0_1700083476522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shadowtwin41_finetuned_squad_accelerate","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shadowtwin41_finetuned_squad_accelerate","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_shadowtwin41_finetuned_squad_accelerate|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ShadowTwin41/bert-finetuned-squad-accelerate
\ No newline at end of file

From 2fb5db5354ca5b43f2f01a2da2d447dd72c1e029 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:25:44 +0700
Subject: [PATCH 133/408] Add model
 2023-11-15-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en

---
 ..._uncased_finetuned_lr_2e_05_epochs_3_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en.md
new file mode 100644
index 00000000000000..1101a45a3fd5af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from husnu)
+author: John Snow Labs
+name: bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l6-h256-uncased-finetuned_lr-2e-05_epochs-3` is a English model orginally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en_5.2.0_3.0_1700083536001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3_en_5.2.0_3.0_1700083536001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.xtremedistiled_uncased_lr_2e_05_epochs_3.by_husnu").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|47.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/xtremedistil-l6-h256-uncased-finetuned_lr-2e-05_epochs-3
\ No newline at end of file

From a7f62894bd73fc2c929730ce7547b3609c8a6bf0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:27:05 +0700
Subject: [PATCH 134/408] Add model
 2023-11-15-bert_qa_roberta_base_chinese_extractive_zh

---
 ...t_qa_roberta_base_chinese_extractive_zh.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_zh.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_zh.md
new file mode 100644
index 00000000000000..5ced75aa0828e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_zh.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Chinese BertForQuestionAnswering Base Cased model (from jackh1995)
+author: John Snow Labs
+name: bert_qa_roberta_base_chinese_extractive
+date: 2023-11-15
+tags: [zh, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-chinese-extractive-qa` is a Chinese model originally trained by `jackh1995`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_chinese_extractive_zh_5.2.0_3.0_1700083617267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_chinese_extractive_zh_5.2.0_3.0_1700083617267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_roberta_base_chinese_extractive","zh") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["PUT YOUR QUESTION HERE", "PUT YOUR CONTEXT HERE"]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_roberta_base_chinese_extractive","zh") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("PUT YOUR QUESTION HERE", "PUT YOUR CONTEXT HERE").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("zh.answer_question.bert.base_extractive").predict("""PUT YOUR QUESTION HERE|||"PUT YOUR CONTEXT HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_roberta_base_chinese_extractive|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|zh|
+|Size:|380.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/jackh1995/roberta-base-chinese-extractive-qa
\ No newline at end of file

From 19fae5e5ae9663ff1fce38088e4460731fd1281e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:30:27 +0700
Subject: [PATCH 135/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en

---
 ...ew_shot_k_64_finetuned_squad_seed_10_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en.md
new file mode 100644
index 00000000000000..3ff3cb4f931e48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-10` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en_5.2.0_3.0_1700083820750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10_en_5.2.0_3.0_1700083820750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_64d_seed_10").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|378.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-10
\ No newline at end of file

From ba11153bdda1b7a5aa193b3062193ea3a24d8b77 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:52:29 +0700
Subject: [PATCH 136/408] Add model
 2023-11-15-bert_qa_shanny_finetuned_squad_en

---
 ...11-15-bert_qa_shanny_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_shanny_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shanny_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shanny_finetuned_squad_en.md
new file mode 100644
index 00000000000000..2ae57f392f259a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_shanny_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from Shanny)
+author: John Snow Labs
+name: bert_qa_shanny_finetuned_squad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `Shanny`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_shanny_finetuned_squad_en_5.2.0_3.0_1700085140357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_shanny_finetuned_squad_en_5.2.0_3.0_1700085140357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shanny_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shanny_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_shanny_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Shanny/bert-finetuned-squad
\ No newline at end of file

From be45f929550012c2e318f5a62d2082c9815d8cde Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 04:59:35 +0700
Subject: [PATCH 137/408] Add model
 2023-11-15-bert_qa_roberta_base_chinese_extractive_qa_zh

---
 ...a_roberta_base_chinese_extractive_qa_zh.md | 113 ++++++++++++++++++
 1 file changed, 113 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_qa_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_qa_zh.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_qa_zh.md
new file mode 100644
index 00000000000000..749ca884f61590
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_base_chinese_extractive_qa_zh.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: Chinese BertForQuestionAnswering model (from uer)
+author: John Snow Labs
+name: bert_qa_roberta_base_chinese_extractive_qa
+date: 2023-11-15
+tags: [zh, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-chinese-extractive-qa` is a Chinese model orginally trained by `uer`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_chinese_extractive_qa_zh_5.2.0_3.0_1700085567946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_chinese_extractive_qa_zh_5.2.0_3.0_1700085567946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_roberta_base_chinese_extractive_qa","zh") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_roberta_base_chinese_extractive_qa","zh")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("zh.answer_question.bert.base.by_uer").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_roberta_base_chinese_extractive_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|zh|
+|Size:|380.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/uer/roberta-base-chinese-extractive-qa
+- https://spaces.ac.cn/archives/4338
+- https://www.kesci.com/home/competition/5d142d8cbb14e6002c04e14a/content/0
+- https://github.com/dbiir/UER-py/
+- https://cloud.tencent.com/product/tione/
+- https://github.com/ymcui/cmrc2018
\ No newline at end of file

From ef4ec2159728967cd3435205302cbf3edc8e1782 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 05:04:21 +0700
Subject: [PATCH 138/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en

---
 ...few_shot_k_64_finetuned_squad_seed_2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..b313cb6e49742e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-2` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en_5.2.0_3.0_1700085853659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2_en_5.2.0_3.0_1700085853659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_64d_seed_2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|378.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-2
\ No newline at end of file

From 438e7744acb4caee5b99f671c2f4aaf3dd53090f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 05:22:02 +0700
Subject: [PATCH 139/408] Add model 2023-11-15-bert_qa_small_finetuned_cuad_en

---
 ...3-11-15-bert_qa_small_finetuned_cuad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_en.md
new file mode 100644
index 00000000000000..3af4cc39fd35a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Small Cased model (from muhtasham)
+author: John Snow Labs
+name: bert_qa_small_finetuned_cuad
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-small-finetuned-cuad` is a English model originally trained by `muhtasham`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_small_finetuned_cuad_en_5.2.0_3.0_1700086918408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_small_finetuned_cuad_en_5.2.0_3.0_1700086918408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_small_finetuned_cuad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_small_finetuned_cuad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_small_finetuned_cuad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|107.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/muhtasham/bert-small-finetuned-cuad
\ No newline at end of file

From 9d6da71643d7a2a7c8c226b9f15e1d741cb2e35e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 05:45:20 +0700
Subject: [PATCH 140/408] Add model
 2023-11-15-bert_qa_small_finetuned_cuad_full_longer_en

---
 ..._qa_small_finetuned_cuad_full_longer_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_full_longer_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_full_longer_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_full_longer_en.md
new file mode 100644
index 00000000000000..0dab11594609a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_small_finetuned_cuad_full_longer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Small Cased model (from muhtasham)
+author: John Snow Labs
+name: bert_qa_small_finetuned_cuad_full_longer
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-small-finetuned-cuad-full-longer` is a English model originally trained by `muhtasham`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_small_finetuned_cuad_full_longer_en_5.2.0_3.0_1700088314621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_small_finetuned_cuad_full_longer_en_5.2.0_3.0_1700088314621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_small_finetuned_cuad_full_longer","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_small_finetuned_cuad_full_longer","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_small_finetuned_cuad_full_longer|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|107.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/muhtasham/bert-small-finetuned-cuad-full-longer
\ No newline at end of file

From b877b8f4a824e0067bb1d7d58aff92e105d0be56 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 06:05:27 +0700
Subject: [PATCH 141/408] Add model 2023-11-15-bert_qa_roberta_test_en

---
 .../2023-11-15-bert_qa_roberta_test_en.md     | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_test_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_test_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_test_en.md
new file mode 100644
index 00000000000000..e34ecb105d0015
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_roberta_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from vvincentt)
+author: John Snow Labs
+name: bert_qa_roberta_test
+date: 2023-11-15
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta_test` is a English model originally trained by `vvincentt`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_test_en_5.2.0_3.0_1700089519451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_test_en_5.2.0_3.0_1700089519451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_roberta_test","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_roberta_test","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_roberta_test|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/vvincentt/roberta_test
\ No newline at end of file

From 610cf375f348c43fb9fc909ad45c7e413a80936d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 06:07:46 +0700
Subject: [PATCH 142/408] Add model
 2023-11-15-bert_qa_spanbert_finetuned_squadv2_en

---
 ...5-bert_qa_spanbert_finetuned_squadv2_en.md | 114 ++++++++++++++++++
 1 file changed, 114 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_finetuned_squadv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..190c4f689a2f6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_finetuned_squadv2_en.md
@@ -0,0 +1,114 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from mrm8488)
+author: John Snow Labs
+name: bert_qa_spanbert_finetuned_squadv2
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-finetuned-squadv2` is a English model orginally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_finetuned_squadv2_en_5.2.0_3.0_1700089654562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_finetuned_squadv2_en_5.2.0_3.0_1700089654562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_finetuned_squadv2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_finetuned_squadv2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.span_bert.v2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/spanbert-finetuned-squadv2
+- https://arxiv.org/abs/1907.10529
+- https://twitter.com/mrm8488
+- https://github.com/facebookresearch
+- https://github.com/facebookresearch/SpanBERT
+- https://github.com/facebookresearch/SpanBERT#pre-trained-models
+- https://rajpurkar.github.io/SQuAD-explorer/
\ No newline at end of file

From b33e3bf84e08062928d6b33a6c16db365dc0595a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 06:08:58 +0700
Subject: [PATCH 143/408] Add model
 2023-11-15-electra_qa_araelectra_discriminator_soqal_ar

---
 ...ra_qa_araelectra_discriminator_soqal_ar.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-electra_qa_araelectra_discriminator_soqal_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-electra_qa_araelectra_discriminator_soqal_ar.md b/docs/_posts/ahmedlone127/2023-11-15-electra_qa_araelectra_discriminator_soqal_ar.md
new file mode 100644
index 00000000000000..fd6664d63b5bf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-electra_qa_araelectra_discriminator_soqal_ar.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: Arabic electra_qa_araelectra_discriminator_soqal BertForQuestionAnswering from Damith
+author: John Snow Labs
+name: electra_qa_araelectra_discriminator_soqal
+date: 2023-11-15
+tags: [bert, ar, open_source, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_araelectra_discriminator_soqal` is a Arabic model originally trained by Damith.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_araelectra_discriminator_soqal_ar_5.2.0_3.0_1700089728517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_araelectra_discriminator_soqal_ar_5.2.0_3.0_1700089728517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_araelectra_discriminator_soqal","ar") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_araelectra_discriminator_soqal", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_araelectra_discriminator_soqal|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|504.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/Damith/AraELECTRA-discriminator-SOQAL
\ No newline at end of file

From 6590224e6f074aec8102c98d362094eedcd8ad2b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 06:15:28 +0700
Subject: [PATCH 144/408] Add model
 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en

---
 ..._shot_k_1024_finetuned_squad_seed_42_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en.md b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en.md
new file mode 100644
index 00000000000000..5690a0ff9a4a3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42
+date: 2023-11-15
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-42` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en_5.2.0_3.0_1700090111484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42_en_5.2.0_3.0_1700090111484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_1024d_seed_42").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_42|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|394.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-42
\ No newline at end of file

From df36807e22ce71e0c9a29de34b9bfb13fb1364c6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 06:18:15 +0700
Subject: [PATCH 145/408] Add model 2023-11-15-electra_qa_base_chaii_en

---
 .../2023-11-15-electra_qa_base_chaii_en.md    | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-15-electra_qa_base_chaii_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-15-electra_qa_base_chaii_en.md b/docs/_posts/ahmedlone127/2023-11-15-electra_qa_base_chaii_en.md
new file mode 100644
index 00000000000000..976afd85711bce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-15-electra_qa_base_chaii_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from SauravMaheshkar)
+author: John Snow Labs
+name: electra_qa_base_chaii
+date: 2023-11-15
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-chaii` is a English model originally trained by `SauravMaheshkar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_chaii_en_5.2.0_3.0_1700090287058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_chaii_en_5.2.0_3.0_1700090287058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_chaii","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_chaii","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.chaii.electra.base").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_chaii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/SauravMaheshkar/electra-base-chaii
\ No newline at end of file

From 94b84753965f8a0de1dd56c230265da56905d02e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 07:29:42 +0700
Subject: [PATCH 146/408] Add model
 2023-11-16-electra_qa_base_v2_finetuned_korquad_ko

---
 ...electra_qa_base_v2_finetuned_korquad_ko.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v2_finetuned_korquad_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v2_finetuned_korquad_ko.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v2_finetuned_korquad_ko.md
new file mode 100644
index 00000000000000..943f1db69c0ae0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v2_finetuned_korquad_ko.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Korean ElectraForQuestionAnswering model (from monologg)
+author: John Snow Labs
+name: electra_qa_base_v2_finetuned_korquad
+date: 2023-11-16
+tags: [ko, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `koelectra-base-v2-finetuned-korquad` is a Korean model originally trained by `monologg`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_v2_finetuned_korquad_ko_5.2.0_3.0_1700094573912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_v2_finetuned_korquad_ko_5.2.0_3.0_1700094573912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_v2_finetuned_korquad","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_v2_finetuned_korquad","ko") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.korquad.electra.base_v2.by_monologg").predict("""내 이름은 무엇입니까?|||"제 이름은 클라라이고 저는 버클리에 살고 있습니다.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_v2_finetuned_korquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|411.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/monologg/koelectra-base-v2-finetuned-korquad
\ No newline at end of file

From 8d4984aed9da0fed426ed0a1504eaf498e307446 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 07:34:23 +0700
Subject: [PATCH 147/408] Add model 2023-11-16-bert_qa_tiny_en

---
 .../2023-11-16-bert_qa_tiny_en.md             | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_en.md
new file mode 100644
index 00000000000000..74f0a6eb0a2a6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny Cased model (from srcocotero)
+author: John Snow Labs
+name: bert_qa_tiny
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tiny-bert-qa` is a English model originally trained by `srcocotero`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_en_5.2.0_3.0_1700094861529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_en_5.2.0_3.0_1700094861529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tiny","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tiny","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tiny|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/srcocotero/tiny-bert-qa
\ No newline at end of file

From 1a9bf4bd021cbb0cf1fbd4e573a0659622ece7d5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 07:47:09 +0700
Subject: [PATCH 148/408] Add model 2023-11-16-electra_qa_ara_base_artydiqa_ar

---
 ...3-11-16-electra_qa_ara_base_artydiqa_ar.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_ara_base_artydiqa_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_ara_base_artydiqa_ar.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_ara_base_artydiqa_ar.md
new file mode 100644
index 00000000000000..fe40495bdeb336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_ara_base_artydiqa_ar.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Arabic ElectraForQuestionAnswering model (from wissamantoun)
+author: John Snow Labs
+name: electra_qa_ara_base_artydiqa
+date: 2023-11-16
+tags: [ar, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `araelectra-base-artydiqa` is a Arabic model originally trained by `wissamantoun`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_ara_base_artydiqa_ar_5.2.0_3.0_1700095615535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_ara_base_artydiqa_ar_5.2.0_3.0_1700095615535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_ara_base_artydiqa","ar") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["ما هو اسمي؟", "اسمي كلارا وأنا أعيش في بيركلي."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_ara_base_artydiqa","ar") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("ما هو اسمي؟", "اسمي كلارا وأنا أعيش في بيركلي.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ar.answer_question.tydiqa.electra.base").predict("""ما هو اسمي؟|||"اسمي كلارا وأنا أعيش في بيركلي.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_ara_base_artydiqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|504.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/wissamantoun/araelectra-base-artydiqa
\ No newline at end of file

From 3813def71ac81f64e360656d437f963b7dd8d7db Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 07:51:35 +0700
Subject: [PATCH 149/408] Add model
 2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en

---
 ...8_a_2_cord19_200616_squad2_covid_qna_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en.md
new file mode 100644
index 00000000000000..ad1269ffa7c90f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-2_H-128_A-2_cord19-200616_squad2_covid-qna` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en_5.2.0_3.0_1700095892418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna_en_5.2.0_3.0_1700095892418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2_covid_cord19.uncased_2l_128d_a2a_128d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_covid_qna|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.6 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-2_H-128_A-2_cord19-200616_squad2_covid-qna
\ No newline at end of file

From 32e4300d7a37ef7afbbd279f708a9ea663ab361d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 07:53:37 +0700
Subject: [PATCH 150/408] Add model
 2023-11-16-electra_qa_base_v3_discriminator_finetuned_klue_v4_ko

---
 ...e_v3_discriminator_finetuned_klue_v4_ko.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_discriminator_finetuned_klue_v4_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_discriminator_finetuned_klue_v4_ko.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_discriminator_finetuned_klue_v4_ko.md
new file mode 100644
index 00000000000000..c001a9eda4ef20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_discriminator_finetuned_klue_v4_ko.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Korean ElectraForQuestionAnswering model (from obokkkk)
+author: John Snow Labs
+name: electra_qa_base_v3_discriminator_finetuned_klue_v4
+date: 2023-11-16
+tags: [ko, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `koelectra-base-v3-discriminator-finetuned-klue-v4` is a Korean model originally trained by `obokkkk`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_v3_discriminator_finetuned_klue_v4_ko_5.2.0_3.0_1700096009029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_v3_discriminator_finetuned_klue_v4_ko_5.2.0_3.0_1700096009029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_v3_discriminator_finetuned_klue_v4","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_v3_discriminator_finetuned_klue_v4","ko") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.klue.electra.base.by_obokkkk").predict("""내 이름은 무엇입니까?|||"제 이름은 클라라이고 저는 버클리에 살고 있습니다.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_v3_discriminator_finetuned_klue_v4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|419.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/obokkkk/koelectra-base-v3-discriminator-finetuned-klue-v4
\ No newline at end of file

From c9ffc887be1db0c243843d17dbd1474284de4149 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 07:56:06 +0700
Subject: [PATCH 151/408] Add model
 2023-11-16-bert_qa_sasuke_finetuned_squad_en

---
 ...11-16-bert_qa_sasuke_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_sasuke_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sasuke_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sasuke_finetuned_squad_en.md
new file mode 100644
index 00000000000000..75e0fc873f47b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sasuke_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from sasuke)
+author: John Snow Labs
+name: bert_qa_sasuke_finetuned_squad
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `sasuke`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sasuke_finetuned_squad_en_5.2.0_3.0_1700096158969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sasuke_finetuned_squad_en_5.2.0_3.0_1700096158969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_sasuke_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_sasuke_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sasuke_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/sasuke/bert-finetuned-squad
\ No newline at end of file

From 0b15d40d70bcf84587de194ffb0241e082186bf2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:00:35 +0700
Subject: [PATCH 152/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en

---
 ...ew_shot_k_16_finetuned_squad_seed_10_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en.md
new file mode 100644
index 00000000000000..bb7669d6e431f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-10` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en_5.2.0_3.0_1700096426899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10_en_5.2.0_3.0_1700096426899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_10_base_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|375.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-10
\ No newline at end of file

From b55339b25a666d30e091bb9e315a9f952a5773eb Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:14:10 +0700
Subject: [PATCH 153/408] Add model
 2023-11-16-electra_qa_base_finetuned_squadv1_en

---
 ...16-electra_qa_base_finetuned_squadv1_en.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_finetuned_squadv1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..fcb9a1bd61f7f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_finetuned_squadv1_en.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from mrm8488)
+author: John Snow Labs
+name: electra_qa_base_finetuned_squadv1
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-finetuned-squadv1` is a English model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_finetuned_squadv1_en_5.2.0_3.0_1700097241442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_finetuned_squadv1_en_5.2.0_3.0_1700097241442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_finetuned_squadv1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_finetuned_squadv1","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.base.by_mrm8488").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/electra-base-finetuned-squadv1
+- https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/
\ No newline at end of file

From af458d91f55ba88be6e0f1673097c85618c5abc1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:16:47 +0700
Subject: [PATCH 154/408] Add model
 2023-11-16-bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en

---
 ...2_a_8_cord19_200616_squad2_covid_qna_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en.md
new file mode 100644
index 00000000000000..322a4ca305de68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-2_H-512_A-8_cord19-200616_squad2_covid-qna` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en_5.2.0_3.0_1700097405458.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna_en_5.2.0_3.0_1700097405458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2_covid_cord19.uncased_2l_512d_a8a_512d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_2_h_512_a_8_cord19_200616_squad2_covid_qna|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|83.3 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-2_H-512_A-8_cord19-200616_squad2_covid-qna
\ No newline at end of file

From 117fb974bcaddad331eb12560841f27b40aaea6c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:22:00 +0700
Subject: [PATCH 155/408] Add model 2023-11-16-bert_qa_sd1_small_en

---
 .../2023-11-16-bert_qa_sd1_small_en.md        | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_sd1_small_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sd1_small_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sd1_small_en.md
new file mode 100644
index 00000000000000..36e6b1104a3531
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sd1_small_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Small Cased model (from motiondew)
+author: John Snow Labs
+name: bert_qa_sd1_small
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-sd1-small` is a English model originally trained by `motiondew`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sd1_small_en_5.2.0_3.0_1700097709617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sd1_small_en_5.2.0_3.0_1700097709617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sd1_small","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_sd1_small","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.small").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sd1_small|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/motiondew/bert-sd1-small
\ No newline at end of file

From 95a70d3ad87f1893b4f2a852c82b28bb2eb28d66 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:22:59 +0700
Subject: [PATCH 156/408] Add model
 2023-11-16-electra_qa_base_v3_finetuned_korquad_ko

---
 ...electra_qa_base_v3_finetuned_korquad_ko.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_finetuned_korquad_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_finetuned_korquad_ko.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_finetuned_korquad_ko.md
new file mode 100644
index 00000000000000..765dbeb11e127b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_v3_finetuned_korquad_ko.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Korean ElectraForQuestionAnswering model (from monologg) Version-3
+author: John Snow Labs
+name: electra_qa_base_v3_finetuned_korquad
+date: 2023-11-16
+tags: [ko, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `koelectra-base-v3-finetuned-korquad` is a Korean model originally trained by `monologg`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_v3_finetuned_korquad_ko_5.2.0_3.0_1700097709677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_v3_finetuned_korquad_ko_5.2.0_3.0_1700097709677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_v3_finetuned_korquad","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_v3_finetuned_korquad","ko") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.korquad.electra.base").predict("""내 이름은 무엇입니까?|||"제 이름은 클라라이고 저는 버클리에 살고 있습니다.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_v3_finetuned_korquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|419.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/monologg/koelectra-base-v3-finetuned-korquad
\ No newline at end of file

From d0868dd2925c4f35d3fe17e3dc66381aaa68a46a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:31:03 +0700
Subject: [PATCH 157/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en

---
 ...w_shot_k_256_finetuned_squad_seed_10_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en.md
new file mode 100644
index 00000000000000..06a10de7b0a4c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-10` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en_5.2.0_3.0_1700098256022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10_en_5.2.0_3.0_1700098256022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_256d_seed_10").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|383.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-10
\ No newline at end of file

From 04f8b20beebfbbfe52be691b17d7da3f8047ec75 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:40:59 +0700
Subject: [PATCH 158/408] Add model 2023-11-16-electra_qa_base_squad2_en

---
 .../2023-11-16-electra_qa_base_squad2_en.md   | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_en.md
new file mode 100644
index 00000000000000..63fa816f7aeb42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_en.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from navteca)
+author: John Snow Labs
+name: electra_qa_base_squad2
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-squad2` is a English model originally trained by `navteca`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_squad2_en_5.2.0_3.0_1700098850923.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_squad2_en_5.2.0_3.0_1700098850923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_squad2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_squad2","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.electra.base.by_navteca").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/navteca/electra-base-squad2
+- https://rajpurkar.github.io/SQuAD-explorer/
\ No newline at end of file

From 011cbf809f639e926e06258539beff89971096a9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:44:37 +0700
Subject: [PATCH 159/408] Add model
 2023-11-16-bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en

---
 ...a_set_date_3_lr_3e_5_bosnian_32_ep_3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en.md
new file mode 100644
index 00000000000000..20e6c7f548dd2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3 BertForQuestionAnswering from motiondew
+author: John Snow Labs
+name: bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3` is a English model originally trained by motiondew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700099070600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3_en_5.2.0_3.0_1700099070600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_set_date_3_lr_3e_5_bosnian_32_ep_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/motiondew/bert-set_date_3-lr-3e-5-bs-32-ep-3
\ No newline at end of file

From 098da331a00f6a45871994f32756c17a132e3495 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:48:38 +0700
Subject: [PATCH 160/408] Add model 2023-11-16-electra_qa_g_base_germanquad_de

---
 ...3-11-16-electra_qa_g_base_germanquad_de.md | 105 ++++++++++++++++++
 1 file changed, 105 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_de.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_de.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_de.md
new file mode 100644
index 00000000000000..7a5115cccea657
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_de.md
@@ -0,0 +1,105 @@
+---
+layout: model
+title: German ElectraForQuestionAnswering model (from deepset)
+author: John Snow Labs
+name: electra_qa_g_base_germanquad
+date: 2023-11-16
+tags: [de, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: de
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `gelectra-base-germanquad` is a German model originally trained by `deepset`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_g_base_germanquad_de_5.2.0_3.0_1700099310383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_g_base_germanquad_de_5.2.0_3.0_1700099310383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_g_base_germanquad","de") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Was ist mein Name?", "Mein Name ist Clara und ich lebe in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_g_base_germanquad","de") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Was ist mein Name?", "Mein Name ist Clara und ich lebe in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.answer_question.electra.base").predict("""Was ist mein Name?|||"Mein Name ist Clara und ich lebe in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_g_base_germanquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|de|
+|Size:|410.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/gelectra-base-germanquad
+- https://deepset.ai/germanquad
+- https://deepset.ai/german-bert
+- https://github.com/deepset-ai/FARM
+- https://github.com/deepset-ai/haystack/
+- https://haystack.deepset.ai/community/join
\ No newline at end of file

From 41456709f6970f3bf5f8c4570db7d21efbb3f053 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:56:09 +0700
Subject: [PATCH 161/408] Add model
 2023-11-16-bert_qa_vuiseng9_bert_base_uncased_squad_en

---
 ..._qa_vuiseng9_bert_base_uncased_squad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_vuiseng9_bert_base_uncased_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_vuiseng9_bert_base_uncased_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_vuiseng9_bert_base_uncased_squad_en.md
new file mode 100644
index 00000000000000..3c559cf0aadb4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_vuiseng9_bert_base_uncased_squad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from vuiseng9)
+author: John Snow Labs
+name: bert_qa_vuiseng9_bert_base_uncased_squad
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-squad` is a English model orginally trained by `vuiseng9`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_vuiseng9_bert_base_uncased_squad_en_5.2.0_3.0_1700099761022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_vuiseng9_bert_base_uncased_squad_en_5.2.0_3.0_1700099761022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_vuiseng9_bert_base_uncased_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_vuiseng9_bert_base_uncased_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.base_uncased.by_vuiseng9").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_vuiseng9_bert_base_uncased_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/vuiseng9/bert-base-uncased-squad
\ No newline at end of file

From 30bdb47b55d9493f11f41f8e656907bae14e3fb3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 08:58:44 +0700
Subject: [PATCH 162/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en

---
 ...ew_shot_k_256_finetuned_squad_seed_4_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..dcf80385735cf5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-4` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en_5.2.0_3.0_1700099917692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4_en_5.2.0_3.0_1700099917692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_4_base_256d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|383.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-4
\ No newline at end of file

From 7681c1d7ecd384f5ee493611a0b4b9e0da2ed82b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:13:51 +0700
Subject: [PATCH 163/408] Add model
 2023-11-16-bert_qa_shashank1303_finetuned_squad_accelerate_en

---
 ...shank1303_finetuned_squad_accelerate_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_shashank1303_finetuned_squad_accelerate_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_shashank1303_finetuned_squad_accelerate_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_shashank1303_finetuned_squad_accelerate_en.md
new file mode 100644
index 00000000000000..f97da78402b483
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_shashank1303_finetuned_squad_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from shashank1303)
+author: John Snow Labs
+name: bert_qa_shashank1303_finetuned_squad_accelerate
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad-accelerate` is a English model originally trained by `shashank1303`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_shashank1303_finetuned_squad_accelerate_en_5.2.0_3.0_1700100817571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_shashank1303_finetuned_squad_accelerate_en_5.2.0_3.0_1700100817571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shashank1303_finetuned_squad_accelerate","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_shashank1303_finetuned_squad_accelerate","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_shashank1303_finetuned_squad_accelerate|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/shashank1303/bert-finetuned-squad-accelerate
\ No newline at end of file

From 25c6ecf7f7302a0a34c352bbd5a266ca0a9d68a9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:14:51 +0700
Subject: [PATCH 164/408] Add model
 2023-11-16-electra_qa_g_base_germanquad_distilled_de

---
 ...ectra_qa_g_base_germanquad_distilled_de.md | 105 ++++++++++++++++++
 1 file changed, 105 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_distilled_de.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_distilled_de.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_distilled_de.md
new file mode 100644
index 00000000000000..62ae0aa9815164
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_g_base_germanquad_distilled_de.md
@@ -0,0 +1,105 @@
+---
+layout: model
+title: German ElectraForQuestionAnswering Distilled model (from deepset)
+author: John Snow Labs
+name: electra_qa_g_base_germanquad_distilled
+date: 2023-11-16
+tags: [de, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: de
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `gelectra-base-germanquad-distilled` is a German model originally trained by `deepset`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_g_base_germanquad_distilled_de_5.2.0_3.0_1700100818667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_g_base_germanquad_distilled_de_5.2.0_3.0_1700100818667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_g_base_germanquad_distilled","de") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Was ist mein Name?", "Mein Name ist Clara und ich lebe in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_g_base_germanquad_distilled","de") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Was ist mein Name?", "Mein Name ist Clara und ich lebe in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.answer_question.electra.distilled_base").predict("""Was ist mein Name?|||"Mein Name ist Clara und ich lebe in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_g_base_germanquad_distilled|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|de|
+|Size:|410.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/gelectra-base-germanquad-distilled
+- https://deepset.ai/germanquad
+- https://deepset.ai/german-bert
+- https://github.com/deepset-ai/FARM
+- https://github.com/deepset-ai/haystack/
+- https://haystack.deepset.ai/community/join
\ No newline at end of file

From d42825df04bfccd820bf6ec174fcf6c4864a4c25 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:15:52 +0700
Subject: [PATCH 165/408] Add model 2023-11-16-electra_qa_klue_mrc_base_ko

---
 .../2023-11-16-electra_qa_klue_mrc_base_ko.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_klue_mrc_base_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_klue_mrc_base_ko.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_klue_mrc_base_ko.md
new file mode 100644
index 00000000000000..19991a104b6751
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_klue_mrc_base_ko.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Korean ElectraForQuestionAnswering model (from seongju)
+author: John Snow Labs
+name: electra_qa_klue_mrc_base
+date: 2023-11-16
+tags: [ko, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `klue-mrc-koelectra-base` is a Korean model originally trained by `seongju`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_klue_mrc_base_ko_5.2.0_3.0_1700100936675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_klue_mrc_base_ko_5.2.0_3.0_1700100936675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_klue_mrc_base","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_klue_mrc_base","ko") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.klue.electra.base").predict("""내 이름은 무엇입니까?|||"제 이름은 클라라이고 저는 버클리에 살고 있습니다.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_klue_mrc_base|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|419.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/seongju/klue-mrc-koelectra-base
\ No newline at end of file

From d5858f7012962f1cb167a38d43c40daa43759733 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:24:10 +0700
Subject: [PATCH 166/408] Add model
 2023-11-16-bert_qa_wiselinjayajos_finetuned_squad_en

---
 ...rt_qa_wiselinjayajos_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_wiselinjayajos_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_wiselinjayajos_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_wiselinjayajos_finetuned_squad_en.md
new file mode 100644
index 00000000000000..cb23f61c28da35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_wiselinjayajos_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from wiselinjayajos)
+author: John Snow Labs
+name: bert_qa_wiselinjayajos_finetuned_squad
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `wiselinjayajos`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_wiselinjayajos_finetuned_squad_en_5.2.0_3.0_1700101442486.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_wiselinjayajos_finetuned_squad_en_5.2.0_3.0_1700101442486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_wiselinjayajos_finetuned_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_wiselinjayajos_finetuned_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.finetuned.by_wiselinjayajos").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_wiselinjayajos_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/wiselinjayajos/bert-finetuned-squad
\ No newline at end of file

From 8df7b73eb2bcaa8239b9acfb37b0a6a38cdaab84 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:29:27 +0700
Subject: [PATCH 167/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en

---
 ...few_shot_k_64_finetuned_squad_seed_6_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..db467a9ff38acf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-6` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en_5.2.0_3.0_1700101758893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6_en_5.2.0_3.0_1700101758893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_64d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|378.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-6
\ No newline at end of file

From 2f653bef815bb972cf6f776d29e18d0bd7920737 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:33:25 +0700
Subject: [PATCH 168/408] Add model
 2023-11-16-electra_qa_small_finetuned_squadv1_en

---
 ...6-electra_qa_small_finetuned_squadv1_en.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..361b4356a237c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv1_en.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering Small model (from mrm8488)
+author: John Snow Labs
+name: electra_qa_small_finetuned_squadv1
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-small-finetuned-squadv1` is a English model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_small_finetuned_squadv1_en_5.2.0_3.0_1700102000508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_small_finetuned_squadv1_en_5.2.0_3.0_1700102000508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_small_finetuned_squadv1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_small_finetuned_squadv1","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.small").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_small_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/electra-small-finetuned-squadv1
+- https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/
\ No newline at end of file

From 79dc258c075845c07518662c43d0affe460979bf Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:34:25 +0700
Subject: [PATCH 169/408] Add model
 2023-11-16-bert_qa_small_finetuned_cuad_full_en

---
 ...16-bert_qa_small_finetuned_cuad_full_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_small_finetuned_cuad_full_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_small_finetuned_cuad_full_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_small_finetuned_cuad_full_en.md
new file mode 100644
index 00000000000000..6138dc190360ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_small_finetuned_cuad_full_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Small Cased model (from muhtasham)
+author: John Snow Labs
+name: bert_qa_small_finetuned_cuad_full
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-small-finetuned-cuad-full` is a English model originally trained by `muhtasham`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_small_finetuned_cuad_full_en_5.2.0_3.0_1700102019793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_small_finetuned_cuad_full_en_5.2.0_3.0_1700102019793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_small_finetuned_cuad_full","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_small_finetuned_cuad_full","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_small_finetuned_cuad_full|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|107.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/muhtasham/bert-small-finetuned-cuad-full
\ No newline at end of file

From 5f414f341c09d3969288e979cca2176317ffc860 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:57:03 +0700
Subject: [PATCH 170/408] Add model 2023-11-16-bert_qa_xquad_thai_mbert_base_th

---
 ...-11-16-bert_qa_xquad_thai_mbert_base_th.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xquad_thai_mbert_base_th.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xquad_thai_mbert_base_th.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xquad_thai_mbert_base_th.md
new file mode 100644
index 00000000000000..cb967029b1e2fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xquad_thai_mbert_base_th.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Thai bert_qa_xquad_thai_mbert_base BertForQuestionAnswering from zhufy
+author: John Snow Labs
+name: bert_qa_xquad_thai_mbert_base
+date: 2023-11-16
+tags: [bert, th, open_source, question_answering, onnx]
+task: Question Answering
+language: th
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_xquad_thai_mbert_base` is a Thai model originally trained by zhufy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xquad_thai_mbert_base_th_5.2.0_3.0_1700103412739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xquad_thai_mbert_base_th_5.2.0_3.0_1700103412739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xquad_thai_mbert_base","th") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_xquad_thai_mbert_base", "th")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xquad_thai_mbert_base|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|th|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/zhufy/xquad-th-mbert-base
\ No newline at end of file

From 7f1f27d9ff8c3783436cbf3dc87807e1b59f4c0b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 09:59:52 +0700
Subject: [PATCH 171/408] Add model
 2023-11-16-bert_qa_spanbert_finetuned_squadv1_en

---
 ...6-bert_qa_spanbert_finetuned_squadv1_en.md | 115 ++++++++++++++++++
 1 file changed, 115 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_finetuned_squadv1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..cf2374846ae537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_finetuned_squadv1_en.md
@@ -0,0 +1,115 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from mrm8488)
+author: John Snow Labs
+name: bert_qa_spanbert_finetuned_squadv1
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-finetuned-squadv1` is a English model orginally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_finetuned_squadv1_en_5.2.0_3.0_1700103584619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_finetuned_squadv1_en_5.2.0_3.0_1700103584619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_finetuned_squadv1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_finetuned_squadv1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/spanbert-finetuned-squadv1
+- https://arxiv.org/abs/1907.10529
+- https://twitter.com/mrm8488
+- https://github.com/facebookresearch
+- https://github.com/facebookresearch/SpanBERT
+- https://github.com/facebookresearch/SpanBERT#pre-trained-models
+- https://rajpurkar.github.io/SQuAD-explorer/
+- https://www.linkedin.com/in/manuel-romero-cs/
\ No newline at end of file

From 4145abd15810ae2c57ce01cc2010c9b684bc9147 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 10:12:07 +0700
Subject: [PATCH 172/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en

---
 ...w_shot_k_1024_finetuned_squad_seed_6_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..a33ab7bfaddcdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-6` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_5.2.0_3.0_1700104318165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_5.2.0_3.0_1700104318165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_1024d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|390.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-1024-finetuned-squad-seed-6
\ No newline at end of file

From 5110452d6813d2dfaa96fef8b7357dfdb756e19d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 10:13:07 +0700
Subject: [PATCH 173/408] Add model 2023-11-16-electra_qa_turkish_tr

---
 .../2023-11-16-electra_qa_turkish_tr.md       | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_turkish_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_turkish_tr.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_turkish_tr.md
new file mode 100644
index 00000000000000..fccd5caaabf9d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_turkish_tr.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Turkish ElectraForQuestionAnswering model (from kuzgunlar)
+author: John Snow Labs
+name: electra_qa_turkish
+date: 2023-11-16
+tags: [tr, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-turkish-qa` is a Turkish model originally trained by `kuzgunlar`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_turkish_tr_5.2.0_3.0_1700104330871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_turkish_tr_5.2.0_3.0_1700104330871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_turkish","tr") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_turkish","tr") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("tr.answer_question.electra").predict("""Benim adım ne?|||"Benim adım Clara ve Berkeley'de yaşıyorum.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_turkish|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|412.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/kuzgunlar/electra-turkish-qa
\ No newline at end of file

From 03ad5283f272e99e2bdde85c71d2d8714bce146a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 10:20:35 +0700
Subject: [PATCH 174/408] Add model
 2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en

---
 ...ed_tquad_finetuned_lr_2e_05_epochs_6_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en.md
new file mode 100644
index 00000000000000..57069ccbca2f4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from husnu)
+author: John Snow Labs
+name: bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l6-h256-uncased-TQUAD-finetuned_lr-2e-05_epochs-6` is a English model originally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en_5.2.0_3.0_1700104833487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6_en_5.2.0_3.0_1700104833487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.tquad.xtremedistiled_uncased_finetuned_epochs_6").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|47.3 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/xtremedistil-l6-h256-uncased-TQUAD-finetuned_lr-2e-05_epochs-6
\ No newline at end of file

From 49b2f2233869975af83da9e94f2d8c086696835f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 10:41:26 +0700
Subject: [PATCH 175/408] Add model
 2023-11-16-bert_base_arabertv2_finetuned_arcd_squad_en

---
 ..._base_arabertv2_finetuned_arcd_squad_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_arabertv2_finetuned_arcd_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_arabertv2_finetuned_arcd_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_arabertv2_finetuned_arcd_squad_en.md
new file mode 100644
index 00000000000000..1f3e2b79aba451
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_arabertv2_finetuned_arcd_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_arabertv2_finetuned_arcd_squad BertForQuestionAnswering from amnahhebrahim
+author: John Snow Labs
+name: bert_base_arabertv2_finetuned_arcd_squad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_finetuned_arcd_squad` is a English model originally trained by amnahhebrahim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_arcd_squad_en_5.2.0_3.0_1700106077088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_arcd_squad_en_5.2.0_3.0_1700106077088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_arabertv2_finetuned_arcd_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_arabertv2_finetuned_arcd_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabertv2_finetuned_arcd_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|504.8 MB|
+
+## References
+
+https://huggingface.co/amnahhebrahim/bert-base-arabertv2-finetuned-arcd-squad
\ No newline at end of file

From fd172d38640a49b2bfd4fdc2e959c92b593ca444 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 10:45:49 +0700
Subject: [PATCH 176/408] Add model
 2023-11-16-electra_qa_small_turkish_uncased_discriminator_finetuned_tr

---
 ...kish_uncased_discriminator_finetuned_tr.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_turkish_uncased_discriminator_finetuned_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_turkish_uncased_discriminator_finetuned_tr.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_turkish_uncased_discriminator_finetuned_tr.md
new file mode 100644
index 00000000000000..4bed1343e6a352
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_turkish_uncased_discriminator_finetuned_tr.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Turkish ElectraForQuestionAnswering model (from husnu)
+author: John Snow Labs
+name: electra_qa_small_turkish_uncased_discriminator_finetuned
+date: 2023-11-16
+tags: [tr, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-small-turkish-uncased-discriminator-finetuned_lr-2e-05_epochs-6` is a Turkish model originally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_small_turkish_uncased_discriminator_finetuned_tr_5.2.0_3.0_1700106346111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_small_turkish_uncased_discriminator_finetuned_tr_5.2.0_3.0_1700106346111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_small_turkish_uncased_discriminator_finetuned","tr") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_small_turkish_uncased_discriminator_finetuned","tr") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("tr.answer_question.electra.small_uncased").predict("""Benim adım ne?|||"Benim adım Clara ve Berkeley'de yaşıyorum.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_small_turkish_uncased_discriminator_finetuned|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|51.6 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/electra-small-turkish-uncased-discriminator-finetuned_lr-2e-05_epochs-6
\ No newline at end of file

From ca50e0b19cca763aff3da397d707469c4749df8c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 10:46:49 +0700
Subject: [PATCH 177/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en

---
 ...ew_shot_k_128_finetuned_squad_seed_4_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..d2bb5ec1d69b62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-4` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en_5.2.0_3.0_1700106348085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4_en_5.2.0_3.0_1700106348085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_128d_seed_4").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|380.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-4
\ No newline at end of file

From 0a92b3219c95f6cd02d90612be8d3d28cb459812 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:03:53 +0700
Subject: [PATCH 178/408] Add model
 2023-11-16-bert_base_chinese_finetuned_squad_en

---
 ...16-bert_base_chinese_finetuned_squad_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_chinese_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_chinese_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_chinese_finetuned_squad_en.md
new file mode 100644
index 00000000000000..b73ea0b151e78d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_chinese_finetuned_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_chinese_finetuned_squad BertForQuestionAnswering from sharkMeow
+author: John Snow Labs
+name: bert_base_chinese_finetuned_squad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_squad` is a English model originally trained by sharkMeow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_squad_en_5.2.0_3.0_1700107426041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_squad_en_5.2.0_3.0_1700107426041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_chinese_finetuned_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_chinese_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_chinese_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/sharkMeow/bert-base-chinese-finetuned-squad
\ No newline at end of file

From 9d1f6ded33ce90ea937fcfd066c2361df1692b19 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:13:00 +0700
Subject: [PATCH 179/408] Add model 2023-11-16-bert_qa_squad1.1_en

---
 .../2023-11-16-bert_qa_squad1.1_en.md         | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad1.1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad1.1_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad1.1_en.md
new file mode 100644
index 00000000000000..bac6fee993bbee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad1.1_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from maroo93)
+author: John Snow Labs
+name: bert_qa_squad1.1
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad1.1` is a English model orginally trained by `maroo93`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad1.1_en_5.2.0_3.0_1700107972423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad1.1_en_5.2.0_3.0_1700107972423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad1.1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_squad1.1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.by_maroo93").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad1.1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/maroo93/squad1.1
\ No newline at end of file

From 7ac31355f170c6dabdf827afb93dc9c0ddc9d39f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:17:11 +0700
Subject: [PATCH 180/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en

---
 ...w_shot_k_128_finetuned_squad_seed_42_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en.md
new file mode 100644
index 00000000000000..c092b915b24e96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-42` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en_5.2.0_3.0_1700108220647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42_en_5.2.0_3.0_1700108220647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_42_base_128d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_42|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|384.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-42
\ No newline at end of file

From 120f76ba46cd39c20bbcd74d98fbf2b5495b0981 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:18:12 +0700
Subject: [PATCH 181/408] Add model 2023-11-16-electra_qa_squad_slp_en

---
 .../2023-11-16-electra_qa_squad_slp_en.md     | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_squad_slp_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_squad_slp_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_squad_slp_en.md
new file mode 100644
index 00000000000000..929d7b39f1881f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_squad_slp_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from rowan1224) Squad
+author: John Snow Labs
+name: electra_qa_squad_slp
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-squad-slp` is a English model originally trained by `rowan1224`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_squad_slp_en_5.2.0_3.0_1700108220754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_squad_slp_en_5.2.0_3.0_1700108220754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_squad_slp","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_squad_slp","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_squad_slp|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/rowan1224/electra-squad-slp
\ No newline at end of file

From 6d4320ca259b66fac1d2f6bfeb37ce1bf3235e1e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:22:24 +0700
Subject: [PATCH 182/408] Add model
 2023-11-16-electra_qa_araelectra_base_finetuned_arcd_ar

---
 ...ra_qa_araelectra_base_finetuned_arcd_ar.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_base_finetuned_arcd_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_base_finetuned_arcd_ar.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_base_finetuned_arcd_ar.md
new file mode 100644
index 00000000000000..60047e95b1ab8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_base_finetuned_arcd_ar.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: Arabic electra_qa_araelectra_base_finetuned_arcd BertForQuestionAnswering from salti
+author: John Snow Labs
+name: electra_qa_araelectra_base_finetuned_arcd
+date: 2023-11-16
+tags: [bert, ar, open_source, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_araelectra_base_finetuned_arcd` is a Arabic model originally trained by salti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_araelectra_base_finetuned_arcd_ar_5.2.0_3.0_1700108532707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_araelectra_base_finetuned_arcd_ar_5.2.0_3.0_1700108532707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_araelectra_base_finetuned_arcd","ar") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_araelectra_base_finetuned_arcd", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_araelectra_base_finetuned_arcd|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|504.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/salti/AraElectra-base-finetuned-ARCD
\ No newline at end of file

From f373fbdbc4fe9ed39b59c984a2522ad3f4cab4c3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:26:17 +0700
Subject: [PATCH 183/408] Add model 2023-11-16-sqoin_qa_model_first_en

---
 .../2023-11-16-sqoin_qa_model_first_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-sqoin_qa_model_first_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-sqoin_qa_model_first_en.md b/docs/_posts/ahmedlone127/2023-11-16-sqoin_qa_model_first_en.md
new file mode 100644
index 00000000000000..bdf1075290b236
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-sqoin_qa_model_first_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English sqoin_qa_model_first BertForQuestionAnswering from Ryan20
+author: John Snow Labs
+name: sqoin_qa_model_first
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sqoin_qa_model_first` is a English model originally trained by Ryan20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sqoin_qa_model_first_en_5.2.0_3.0_1700108770704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sqoin_qa_model_first_en_5.2.0_3.0_1700108770704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("sqoin_qa_model_first","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("sqoin_qa_model_first", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sqoin_qa_model_first|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|405.0 MB|
+
+## References
+
+https://huggingface.co/Ryan20/sqoin_qa_model_first
\ No newline at end of file

From e6293e6ddc4459f3be705901839f2ce9d32b4668 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:38:04 +0700
Subject: [PATCH 184/408] Add model
 2023-11-16-bert_finetuned_squad_quangb1910128_en

---
 ...6-bert_finetuned_squad_quangb1910128_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_quangb1910128_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_quangb1910128_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_quangb1910128_en.md
new file mode 100644
index 00000000000000..f938a98677aca6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_quangb1910128_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_quangb1910128 BertForQuestionAnswering from quangb1910128
+author: John Snow Labs
+name: bert_finetuned_squad_quangb1910128
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_quangb1910128` is a English model originally trained by quangb1910128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_quangb1910128_en_5.2.0_3.0_1700109477106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_quangb1910128_en_5.2.0_3.0_1700109477106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_quangb1910128","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_quangb1910128", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_quangb1910128|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/quangb1910128/bert-finetuned-squad
\ No newline at end of file

From 717e0e9b1bc01c3d1fe3833fd722ec2f59cfa508 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:40:19 +0700
Subject: [PATCH 185/408] Add model 2023-11-16-bert_qa_squad_baseline_en

---
 .../2023-11-16-bert_qa_squad_baseline_en.md   | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_baseline_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_baseline_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_baseline_en.md
new file mode 100644
index 00000000000000..bd139592541b64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_baseline_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from xraychen)
+author: John Snow Labs
+name: bert_qa_squad_baseline
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `squad-baseline` is a English model orginally trained by `xraychen`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_baseline_en_5.2.0_3.0_1700109612502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_baseline_en_5.2.0_3.0_1700109612502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad_baseline","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_squad_baseline","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.base.by_xraychen").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad_baseline|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/xraychen/squad-baseline
\ No newline at end of file

From c279b97224fae8106510cc0efcd53c7357d89ca9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:47:41 +0700
Subject: [PATCH 186/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en

---
 ...few_shot_k_16_finetuned_squad_seed_4_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..a35709e19c89cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-4` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en_5.2.0_3.0_1700110051006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4_en_5.2.0_3.0_1700110051006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_4_base_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|375.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-4
\ No newline at end of file

From eb6ac3af991c21e87a00b6db20dc670d8f11d18f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:48:42 +0700
Subject: [PATCH 187/408] Add model 2023-11-16-braslab_bert_drcd_384_en

---
 .../2023-11-16-braslab_bert_drcd_384_en.md    | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-braslab_bert_drcd_384_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-braslab_bert_drcd_384_en.md b/docs/_posts/ahmedlone127/2023-11-16-braslab_bert_drcd_384_en.md
new file mode 100644
index 00000000000000..2d4b23d4826d0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-braslab_bert_drcd_384_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English braslab_bert_drcd_384 BertForQuestionAnswering from nyust-eb210
+author: John Snow Labs
+name: braslab_bert_drcd_384
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`braslab_bert_drcd_384` is a English model originally trained by nyust-eb210.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/braslab_bert_drcd_384_en_5.2.0_3.0_1700110050448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/braslab_bert_drcd_384_en_5.2.0_3.0_1700110050448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("braslab_bert_drcd_384","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("braslab_bert_drcd_384", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|braslab_bert_drcd_384|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/nyust-eb210/braslab-bert-drcd-384
\ No newline at end of file

From b4fb163da2489f8f751b7aae4217f6433e0f2e55 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 11:49:42 +0700
Subject: [PATCH 188/408] Add model 2023-11-16-electra_qa_biom_base_squad2_en

---
 ...23-11-16-electra_qa_biom_base_squad2_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_base_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_base_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_base_squad2_en.md
new file mode 100644
index 00000000000000..14300f5c4c64b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_base_squad2_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English electra_qa_biom_base_squad2 BertForQuestionAnswering from sultan
+author: John Snow Labs
+name: electra_qa_biom_base_squad2
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_biom_base_squad2` is a English model originally trained by sultan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_biom_base_squad2_en_5.2.0_3.0_1700110050778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_biom_base_squad2_en_5.2.0_3.0_1700110050778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_biom_base_squad2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_biom_base_squad2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_biom_base_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/sultan/BioM-ELECTRA-Base-SQuAD2
\ No newline at end of file

From 5f92aafba277bac1773d4f68296b85d34b72e152 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:02:14 +0700
Subject: [PATCH 189/408] Add model
 2023-11-16-bert_qa_squad_english_bert_base_en

---
 ...1-16-bert_qa_squad_english_bert_base_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_english_bert_base_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_english_bert_base_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_english_bert_base_en.md
new file mode 100644
index 00000000000000..ad4ab9213f758e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_squad_english_bert_base_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_qa_squad_english_bert_base BertForQuestionAnswering from zhufy
+author: John Snow Labs
+name: bert_qa_squad_english_bert_base
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_squad_english_bert_base` is a English model originally trained by zhufy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_squad_english_bert_base_en_5.2.0_3.0_1700110927573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_squad_english_bert_base_en_5.2.0_3.0_1700110927573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_squad_english_bert_base","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_squad_english_bert_base", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_squad_english_bert_base|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/zhufy/squad-en-bert-base
\ No newline at end of file

From fa73385eae57ec6e9eb700cc4ee3460a0820a3c0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:11:30 +0700
Subject: [PATCH 190/408] Add model 2023-11-16-bert_finetuned_squad_shynbui_en

---
 ...3-11-16-bert_finetuned_squad_shynbui_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shynbui_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shynbui_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shynbui_en.md
new file mode 100644
index 00000000000000..d16b04b16919a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shynbui_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_shynbui BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: bert_finetuned_squad_shynbui
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_shynbui` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_shynbui_en_5.2.0_3.0_1700111481730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_shynbui_en_5.2.0_3.0_1700111481730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_shynbui","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_shynbui", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_shynbui|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ShynBui/bert-finetuned-squad
\ No newline at end of file

From 16ef3293f6e514ace6ad9cdadc316ca318d08e74 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:15:30 +0700
Subject: [PATCH 191/408] Add model 2023-11-16-klue_finetuned_squad_kor_v1_ko

---
 ...23-11-16-klue_finetuned_squad_kor_v1_ko.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-klue_finetuned_squad_kor_v1_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-klue_finetuned_squad_kor_v1_ko.md b/docs/_posts/ahmedlone127/2023-11-16-klue_finetuned_squad_kor_v1_ko.md
new file mode 100644
index 00000000000000..8cf59680fd81b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-klue_finetuned_squad_kor_v1_ko.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Korean klue_finetuned_squad_kor_v1 BertForQuestionAnswering from Kdogs
+author: John Snow Labs
+name: klue_finetuned_squad_kor_v1
+date: 2023-11-16
+tags: [bert, ko, open_source, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`klue_finetuned_squad_kor_v1` is a Korean model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/klue_finetuned_squad_kor_v1_ko_5.2.0_3.0_1700111722409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/klue_finetuned_squad_kor_v1_ko_5.2.0_3.0_1700111722409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("klue_finetuned_squad_kor_v1","ko") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("klue_finetuned_squad_kor_v1", "ko")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|klue_finetuned_squad_kor_v1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Kdogs/klue-finetuned-squad_kor_v1
\ No newline at end of file

From 2703a99ff2240a8e50cbd7a9cccc2ce01b81bb7f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:34:22 +0700
Subject: [PATCH 192/408] Add model
 2023-11-16-ntu_adl_span_selection_roberta_en

---
 ...11-16-ntu_adl_span_selection_roberta_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_roberta_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_roberta_en.md b/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_roberta_en.md
new file mode 100644
index 00000000000000..1ff142ed2316fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_roberta_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English ntu_adl_span_selection_roberta BertForQuestionAnswering from xjlulu
+author: John Snow Labs
+name: ntu_adl_span_selection_roberta
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ntu_adl_span_selection_roberta` is a English model originally trained by xjlulu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_roberta_en_5.2.0_3.0_1700112855562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_roberta_en_5.2.0_3.0_1700112855562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ntu_adl_span_selection_roberta","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ntu_adl_span_selection_roberta", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ntu_adl_span_selection_roberta|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/xjlulu/ntu_adl_span_selection_roberta
\ No newline at end of file

From 62a995ffb5b2a4e31d981fab3e1cfce2c24cfa70 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:43:41 +0700
Subject: [PATCH 193/408] Add model 2023-11-16-hubert_qa_milqa_hu

---
 .../2023-11-16-hubert_qa_milqa_hu.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-hubert_qa_milqa_hu.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-hubert_qa_milqa_hu.md b/docs/_posts/ahmedlone127/2023-11-16-hubert_qa_milqa_hu.md
new file mode 100644
index 00000000000000..32ac335ed78eff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-hubert_qa_milqa_hu.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Hungarian hubert_qa_milqa BertForQuestionAnswering from ZTamas
+author: John Snow Labs
+name: hubert_qa_milqa
+date: 2023-11-16
+tags: [bert, hu, open_source, question_answering, onnx]
+task: Question Answering
+language: hu
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_qa_milqa` is a Hungarian model originally trained by ZTamas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_qa_milqa_hu_5.2.0_3.0_1700113413446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_qa_milqa_hu_5.2.0_3.0_1700113413446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hubert_qa_milqa","hu") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hubert_qa_milqa", "hu")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_qa_milqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|hu|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/ZTamas/hubert-qa-milqa
\ No newline at end of file

From fdd550f5689e2f38926787a9fb8ec2f12efc7f1a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:52:18 +0700
Subject: [PATCH 194/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en

---
 ...ew_shot_k_256_finetuned_squad_seed_0_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en.md
new file mode 100644
index 00000000000000..87d326765fa029
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-0` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en_5.2.0_3.0_1700113931035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0_en_5.2.0_3.0_1700113931035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_0_base_256d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_256_finetuned_squad_seed_0|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|383.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-256-finetuned-squad-seed-0
\ No newline at end of file

From 8de5b8b7dcadd255ef04c22e3f796f0ed4eaca30 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 12:56:09 +0700
Subject: [PATCH 195/408] Add model
 2023-11-16-electra_qa_araelectra_squad_arcd_ar

---
 ...-16-electra_qa_araelectra_squad_arcd_ar.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_squad_arcd_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_squad_arcd_ar.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_squad_arcd_ar.md
new file mode 100644
index 00000000000000..86a6b222ec5a90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_araelectra_squad_arcd_ar.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: Arabic electra_qa_araelectra_squad_arcd BertForQuestionAnswering from aymanm419
+author: John Snow Labs
+name: electra_qa_araelectra_squad_arcd
+date: 2023-11-16
+tags: [bert, ar, open_source, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_araelectra_squad_arcd` is a Arabic model originally trained by aymanm419.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_araelectra_squad_arcd_ar_5.2.0_3.0_1700114108717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_araelectra_squad_arcd_ar_5.2.0_3.0_1700114108717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_araelectra_squad_arcd","ar") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_araelectra_squad_arcd", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_araelectra_squad_arcd|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|504.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/aymanm419/araElectra-SQUAD-ARCD
\ No newline at end of file

From 9c847aefa9288c05c6498f1db40be99d5b11e8a8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 13:03:17 +0700
Subject: [PATCH 196/408] Add model
 2023-11-16-batterybert_cased_finetuned_squad_en

---
 ...16-batterybert_cased_finetuned_squad_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-batterybert_cased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-batterybert_cased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-batterybert_cased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..9c1765ca393a87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-batterybert_cased_finetuned_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English batterybert_cased_finetuned_squad BertForQuestionAnswering from HongyangLi
+author: John Snow Labs
+name: batterybert_cased_finetuned_squad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batterybert_cased_finetuned_squad` is a English model originally trained by HongyangLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batterybert_cased_finetuned_squad_en_5.2.0_3.0_1700114589035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batterybert_cased_finetuned_squad_en_5.2.0_3.0_1700114589035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("batterybert_cased_finetuned_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("batterybert_cased_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batterybert_cased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/HongyangLi/batterybert-cased-finetuned-squad
\ No newline at end of file

From e9c0e987aed8f3324db2ac8a3f778c0d8ffccf89 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 13:11:25 +0700
Subject: [PATCH 197/408] Add model
 2023-11-16-distilbert_preguntas_respuestas_posgrados_en

---
 ...lbert_preguntas_respuestas_posgrados_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-distilbert_preguntas_respuestas_posgrados_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-distilbert_preguntas_respuestas_posgrados_en.md b/docs/_posts/ahmedlone127/2023-11-16-distilbert_preguntas_respuestas_posgrados_en.md
new file mode 100644
index 00000000000000..082a00ee2836f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-distilbert_preguntas_respuestas_posgrados_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English distilbert_preguntas_respuestas_posgrados BertForQuestionAnswering from leo123
+author: John Snow Labs
+name: distilbert_preguntas_respuestas_posgrados
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_preguntas_respuestas_posgrados` is a English model originally trained by leo123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_preguntas_respuestas_posgrados_en_5.2.0_3.0_1700115077403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_preguntas_respuestas_posgrados_en_5.2.0_3.0_1700115077403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("distilbert_preguntas_respuestas_posgrados","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("distilbert_preguntas_respuestas_posgrados", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_preguntas_respuestas_posgrados|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/leo123/DistilBERT-Preguntas-Respuestas-Posgrados
\ No newline at end of file

From 09bced6730002dc1ce3c83b5a8ae77a3c111c477 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 13:35:28 +0700
Subject: [PATCH 198/408] Add model 2023-11-16-bert_base_finetuned_klue_mrc_en

---
 ...3-11-16-bert_base_finetuned_klue_mrc_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_finetuned_klue_mrc_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_finetuned_klue_mrc_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_finetuned_klue_mrc_en.md
new file mode 100644
index 00000000000000..6947877cec3402
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_finetuned_klue_mrc_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_finetuned_klue_mrc BertForQuestionAnswering from Forturne
+author: John Snow Labs
+name: bert_base_finetuned_klue_mrc
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_klue_mrc` is a English model originally trained by Forturne.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_klue_mrc_en_5.2.0_3.0_1700116517830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_klue_mrc_en_5.2.0_3.0_1700116517830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_finetuned_klue_mrc","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_finetuned_klue_mrc", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_finetuned_klue_mrc|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Forturne/bert-base-finetuned-klue-mrc
\ No newline at end of file

From d97ac5e39a64c41a20113ffb42a8608d0e169ced Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:02:18 +0700
Subject: [PATCH 199/408] Add model 2023-11-16-legal_bert_base_cuad_en

---
 .../2023-11-16-legal_bert_base_cuad_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-legal_bert_base_cuad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-legal_bert_base_cuad_en.md b/docs/_posts/ahmedlone127/2023-11-16-legal_bert_base_cuad_en.md
new file mode 100644
index 00000000000000..5a394cccbd6761
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-legal_bert_base_cuad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English legal_bert_base_cuad BertForQuestionAnswering from alex-apostolo
+author: John Snow Labs
+name: legal_bert_base_cuad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_bert_base_cuad` is a English model originally trained by alex-apostolo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_base_cuad_en_5.2.0_3.0_1700118130405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_base_cuad_en_5.2.0_3.0_1700118130405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("legal_bert_base_cuad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("legal_bert_base_cuad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_bert_base_cuad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/alex-apostolo/legal-bert-base-cuad
\ No newline at end of file

From b7daf46c1d71827559f90568a36f62e3cdb3e4c7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:04:27 +0700
Subject: [PATCH 200/408] Add model
 2023-11-16-electra_qa_base_discriminator_finetuned_squadv1_en

---
 ...base_discriminator_finetuned_squadv1_en.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv1_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv1_en.md
new file mode 100644
index 00000000000000..443fa5d69b977e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv1_en.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from valhalla)
+author: John Snow Labs
+name: electra_qa_base_discriminator_finetuned_squadv1
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-discriminator-finetuned_squadv1` is a English model originally trained by `valhalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_discriminator_finetuned_squadv1_en_5.2.0_3.0_1700118260213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_discriminator_finetuned_squadv1_en_5.2.0_3.0_1700118260213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_discriminator_finetuned_squadv1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_discriminator_finetuned_squadv1","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.base.by_valhalla").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_discriminator_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/valhalla/electra-base-discriminator-finetuned_squadv1
+- https://github.com/patil-suraj/
\ No newline at end of file

From 77b85bbfaaf2a4b3605e5484410787e595f3d585 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:05:45 +0700
Subject: [PATCH 201/408] Add model
 2023-11-16-burmese_awesome_qa_model_sglasher_en

---
 ...16-burmese_awesome_qa_model_sglasher_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-burmese_awesome_qa_model_sglasher_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-burmese_awesome_qa_model_sglasher_en.md b/docs/_posts/ahmedlone127/2023-11-16-burmese_awesome_qa_model_sglasher_en.md
new file mode 100644
index 00000000000000..947188ed13c0da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-burmese_awesome_qa_model_sglasher_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_sglasher BertForQuestionAnswering from sglasher
+author: John Snow Labs
+name: burmese_awesome_qa_model_sglasher
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_sglasher` is a English model originally trained by sglasher.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_sglasher_en_5.2.0_3.0_1700118329547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_sglasher_en_5.2.0_3.0_1700118329547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("burmese_awesome_qa_model_sglasher","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("burmese_awesome_qa_model_sglasher", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_sglasher|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/sglasher/my_awesome_qa_model
\ No newline at end of file

From 99975b6432abfbf328049c3139ac41a4b520e29e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:28:40 +0700
Subject: [PATCH 202/408] Add model
 2023-11-16-bert_base_french_europeana_cased_squad_french_en

---
 ..._french_europeana_cased_squad_french_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_french_europeana_cased_squad_french_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_french_europeana_cased_squad_french_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_french_europeana_cased_squad_french_en.md
new file mode 100644
index 00000000000000..262c1b379ab887
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_french_europeana_cased_squad_french_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_french_europeana_cased_squad_french BertForQuestionAnswering from Nadav
+author: John Snow Labs
+name: bert_base_french_europeana_cased_squad_french
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_french_europeana_cased_squad_french` is a English model originally trained by Nadav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_french_europeana_cased_squad_french_en_5.2.0_3.0_1700119713022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_french_europeana_cased_squad_french_en_5.2.0_3.0_1700119713022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_french_europeana_cased_squad_french","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_french_europeana_cased_squad_french", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_french_europeana_cased_squad_french|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/Nadav/bert-base-french-europeana-cased-squad-fr
\ No newline at end of file

From 28ae697d6a31804fc79fedbea144ae7de312c592 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:31:48 +0700
Subject: [PATCH 203/408] Add model 2023-11-16-persian_qa_bert_v1_fa

---
 .../2023-11-16-persian_qa_bert_v1_fa.md       | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-persian_qa_bert_v1_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-persian_qa_bert_v1_fa.md b/docs/_posts/ahmedlone127/2023-11-16-persian_qa_bert_v1_fa.md
new file mode 100644
index 00000000000000..2aa4d6bf14aa2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-persian_qa_bert_v1_fa.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Persian persian_qa_bert_v1 BertForQuestionAnswering from SeyedAli
+author: John Snow Labs
+name: persian_qa_bert_v1
+date: 2023-11-16
+tags: [bert, fa, open_source, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_qa_bert_v1` is a Persian model originally trained by SeyedAli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_qa_bert_v1_fa_5.2.0_3.0_1700119804478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_qa_bert_v1_fa_5.2.0_3.0_1700119804478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("persian_qa_bert_v1","fa") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("persian_qa_bert_v1", "fa")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|persian_qa_bert_v1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/SeyedAli/Persian-QA-Bert-V1
\ No newline at end of file

From 526f0e7b7bac9be2a14574a66ab05b2c762fd6d0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:36:30 +0700
Subject: [PATCH 204/408] Add model 2023-11-16-electra_qa_enelpi_squad_tr

---
 .../2023-11-16-electra_qa_enelpi_squad_tr.md  | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_enelpi_squad_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_enelpi_squad_tr.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_enelpi_squad_tr.md
new file mode 100644
index 00000000000000..65e3fda917d2a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_enelpi_squad_tr.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Turkish ElectraForQuestionAnswering model (from enelpi)
+author: John Snow Labs
+name: electra_qa_enelpi_squad
+date: 2023-11-16
+tags: [tr, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-tr-enelpi-squad-qa` is a Turkish model originally trained by `enelpi`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_enelpi_squad_tr_5.2.0_3.0_1700120180540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_enelpi_squad_tr_5.2.0_3.0_1700120180540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_enelpi_squad","tr") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_enelpi_squad","tr") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("tr.answer_question.squad.electra").predict("""Benim adım ne?|||"Benim adım Clara ve Berkeley'de yaşıyorum.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_enelpi_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|412.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/enelpi/electra-tr-enelpi-squad-qa
\ No newline at end of file

From 822390c3fe2c1a6654d4e072cf51cdba1e23bb72 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:41:23 +0700
Subject: [PATCH 205/408] Add model 2023-11-16-bert_qa_tiny_finetuned_cuad_en

---
 ...23-11-16-bert_qa_tiny_finetuned_cuad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_cuad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_cuad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_cuad_en.md
new file mode 100644
index 00000000000000..63a7fb54c76532
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_cuad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny Cased model (from muhtasham)
+author: John Snow Labs
+name: bert_qa_tiny_finetuned_cuad
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-tiny-finetuned-cuad` is a English model originally trained by `muhtasham`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_finetuned_cuad_en_5.2.0_3.0_1700120481223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_finetuned_cuad_en_5.2.0_3.0_1700120481223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tiny_finetuned_cuad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tiny_finetuned_cuad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tiny_finetuned_cuad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/muhtasham/bert-tiny-finetuned-cuad
\ No newline at end of file

From b4de5bceab33bbe864b344cdbd9f5da1376e2784 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 14:50:53 +0700
Subject: [PATCH 206/408] Add model
 2023-11-16-bert_base_uncased_finetuned_nq_finetuned_squad_en

---
 ...uncased_finetuned_nq_finetuned_squad_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_nq_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_nq_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_nq_finetuned_squad_en.md
new file mode 100644
index 00000000000000..068730d71fe787
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_nq_finetuned_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_nq_finetuned_squad BertForQuestionAnswering from leonardoschluter
+author: John Snow Labs
+name: bert_base_uncased_finetuned_nq_finetuned_squad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_nq_finetuned_squad` is a English model originally trained by leonardoschluter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_nq_finetuned_squad_en_5.2.0_3.0_1700121045315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_nq_finetuned_squad_en_5.2.0_3.0_1700121045315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_nq_finetuned_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_nq_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_nq_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/leonardoschluter/bert-base-uncased-finetuned-nq-finetuned-squad
\ No newline at end of file

From 09c95f6012d380a3ea19504bb443e4206ce1aee5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:11:09 +0700
Subject: [PATCH 207/408] Add model 2023-11-16-hw1_span_selection_wwm_ext_en

---
 ...023-11-16-hw1_span_selection_wwm_ext_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-hw1_span_selection_wwm_ext_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-hw1_span_selection_wwm_ext_en.md b/docs/_posts/ahmedlone127/2023-11-16-hw1_span_selection_wwm_ext_en.md
new file mode 100644
index 00000000000000..05394b3c3b0957
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-hw1_span_selection_wwm_ext_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English hw1_span_selection_wwm_ext BertForQuestionAnswering from kyle0518
+author: John Snow Labs
+name: hw1_span_selection_wwm_ext
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_span_selection_wwm_ext` is a English model originally trained by kyle0518.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_span_selection_wwm_ext_en_5.2.0_3.0_1700122263353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_span_selection_wwm_ext_en_5.2.0_3.0_1700122263353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hw1_span_selection_wwm_ext","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hw1_span_selection_wwm_ext", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw1_span_selection_wwm_ext|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.1 MB|
+
+## References
+
+https://huggingface.co/kyle0518/HW1_span_selection_wwm_ext
\ No newline at end of file

From 01d81fdd793759420ab877405f84bebe94f33d62 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:13:35 +0700
Subject: [PATCH 208/408] Add model
 2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en

---
 ...squad2_large_teacher_finetuned_step1_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en.md
new file mode 100644
index 00000000000000..e22b265acb1708
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from MichelBartels)
+author: John Snow Labs
+name: bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tinybert-6l-768d-squad2-large-teacher-finetuned-step1` is a English model orginally trained by `MichelBartels`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en_5.2.0_3.0_1700122406299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1_en_5.2.0_3.0_1700122406299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.large_tiny_768d_v2.by_MichelBartels").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_step1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|249.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/MichelBartels/tinybert-6l-768d-squad2-large-teacher-finetuned-step1
\ No newline at end of file

From eab0ffa7b64b2ff962ff84bac6da7ec6a298bde5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:14:35 +0700
Subject: [PATCH 209/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en

---
 ...ew_shot_k_512_finetuned_squad_seed_8_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..11a605caf300e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-8` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en_5.2.0_3.0_1700122406393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8_en_5.2.0_3.0_1700122406393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_512d_seed_8").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|386.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-8
\ No newline at end of file

From 34bfc64a9d30211e5bea3674c3dfbc7781b56285 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:28:52 +0700
Subject: [PATCH 210/408] Add model
 2023-11-16-chinese_question_answering_jeremyfeng_en

---
 ...hinese_question_answering_jeremyfeng_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-chinese_question_answering_jeremyfeng_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-chinese_question_answering_jeremyfeng_en.md b/docs/_posts/ahmedlone127/2023-11-16-chinese_question_answering_jeremyfeng_en.md
new file mode 100644
index 00000000000000..0d6b023a846157
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-chinese_question_answering_jeremyfeng_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English chinese_question_answering_jeremyfeng BertForQuestionAnswering from JeremyFeng
+author: John Snow Labs
+name: chinese_question_answering_jeremyfeng
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_question_answering_jeremyfeng` is a English model originally trained by JeremyFeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_question_answering_jeremyfeng_en_5.2.0_3.0_1700123320158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_question_answering_jeremyfeng_en_5.2.0_3.0_1700123320158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("chinese_question_answering_jeremyfeng","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("chinese_question_answering_jeremyfeng", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_question_answering_jeremyfeng|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/JeremyFeng/chinese-question-answering
\ No newline at end of file

From 30e59e5895cdfd3a695986df21b6dfac2f53769f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:29:52 +0700
Subject: [PATCH 211/408] Add model 2023-11-16-bert_finetuned_squad_avecoder_en

---
 ...-11-16-bert_finetuned_squad_avecoder_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_avecoder_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_avecoder_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_avecoder_en.md
new file mode 100644
index 00000000000000..0ba03bb271f6d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_avecoder_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_avecoder BertForQuestionAnswering from avecoder
+author: John Snow Labs
+name: bert_finetuned_squad_avecoder
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_avecoder` is a English model originally trained by avecoder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_avecoder_en_5.2.0_3.0_1700123346771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_avecoder_en_5.2.0_3.0_1700123346771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_avecoder","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_avecoder", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_avecoder|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/avecoder/bert-finetuned-squad
\ No newline at end of file

From 21127642db8239e11d55ba6b0e5783daa6f2d8c8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:30:52 +0700
Subject: [PATCH 212/408] Add model
 2023-11-16-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en

---
 ...8_a_2_cord19_200616_squad2_covid_qna_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en.md
new file mode 100644
index 00000000000000..d7700bc451d5f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-6_H-128_A-2_cord19-200616_squad2_covid-qna` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en_5.2.0_3.0_1700123409113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna_en_5.2.0_3.0_1700123409113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2_covid_cord19.uncased_6l_128d_a2a_128d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_6_h_128_a_2_cord19_200616_squad2_covid_qna|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|19.6 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-6_H-128_A-2_cord19-200616_squad2_covid-qna
\ No newline at end of file

From 7351e27a22ec89e73bb660c49d97b22e70a4e0c7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:35:24 +0700
Subject: [PATCH 213/408] Add model
 2023-11-16-electra_qa_google_base_discriminator_squad_en

---
 ...a_qa_google_base_discriminator_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_base_discriminator_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_base_discriminator_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_base_discriminator_squad_en.md
new file mode 100644
index 00000000000000..317c0f541e96dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_base_discriminator_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from Palak)
+author: John Snow Labs
+name: electra_qa_google_base_discriminator_squad
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `google_electra-base-discriminator_squad` is a English model originally trained by `Palak`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_google_base_discriminator_squad_en_5.2.0_3.0_1700123716727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_google_base_discriminator_squad_en_5.2.0_3.0_1700123716727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_google_base_discriminator_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_google_base_discriminator_squad","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.base.by_Palak").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_google_base_discriminator_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Palak/google_electra-base-discriminator_squad
\ No newline at end of file

From 557c5ee4a80e31c9902056d1ddf37d7e22a10cdd Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:40:38 +0700
Subject: [PATCH 214/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en

---
 ...few_shot_k_64_finetuned_squad_seed_8_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..b339645f3b4bf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-8` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en_5.2.0_3.0_1700124031626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8_en_5.2.0_3.0_1700124031626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_8_base_64d_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|378.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-8
\ No newline at end of file

From b66d564755a50085bf121ea533acea100f85735f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:49:37 +0700
Subject: [PATCH 215/408] Add model 2023-11-16-indobert_examqa_id

---
 .../2023-11-16-indobert_examqa_id.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-indobert_examqa_id.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-indobert_examqa_id.md b/docs/_posts/ahmedlone127/2023-11-16-indobert_examqa_id.md
new file mode 100644
index 00000000000000..aa2c71bc5bac7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-indobert_examqa_id.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Indonesian indobert_examqa BertForQuestionAnswering from sinu
+author: John Snow Labs
+name: indobert_examqa
+date: 2023-11-16
+tags: [bert, id, open_source, question_answering, onnx]
+task: Question Answering
+language: id
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_examqa` is a Indonesian model originally trained by sinu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_examqa_id_5.2.0_3.0_1700124569567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_examqa_id_5.2.0_3.0_1700124569567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("indobert_examqa","id") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("indobert_examqa", "id")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_examqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|id|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/sinu/IndoBERT-ExamQA
\ No newline at end of file

From f5c506ed3571a42ea8898664acfc7e8f035736c9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:55:49 +0700
Subject: [PATCH 216/408] Add model 2023-11-16-kazakhbertmulti_squad_kaz_en

---
 ...2023-11-16-kazakhbertmulti_squad_kaz_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-kazakhbertmulti_squad_kaz_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-kazakhbertmulti_squad_kaz_en.md b/docs/_posts/ahmedlone127/2023-11-16-kazakhbertmulti_squad_kaz_en.md
new file mode 100644
index 00000000000000..7cdf5f415d3fa5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-kazakhbertmulti_squad_kaz_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English kazakhbertmulti_squad_kaz BertForQuestionAnswering from Kyrmasch
+author: John Snow Labs
+name: kazakhbertmulti_squad_kaz
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kazakhbertmulti_squad_kaz` is a English model originally trained by Kyrmasch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kazakhbertmulti_squad_kaz_en_5.2.0_3.0_1700124839732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kazakhbertmulti_squad_kaz_en_5.2.0_3.0_1700124839732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("kazakhbertmulti_squad_kaz","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("kazakhbertmulti_squad_kaz", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kazakhbertmulti_squad_kaz|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|609.9 MB|
+
+## References
+
+https://huggingface.co/Kyrmasch/KazakhBERTmulti-SQUAD-kaz
\ No newline at end of file

From 313ec1b0238662d5b79afb933150b1f5a91920ee Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:56:49 +0700
Subject: [PATCH 217/408] Add model
 2023-11-16-electra_qa_google_small_discriminator_squad_en

---
 ..._qa_google_small_discriminator_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_small_discriminator_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_small_discriminator_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_small_discriminator_squad_en.md
new file mode 100644
index 00000000000000..aac16aeb267ff4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_google_small_discriminator_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering Small model (from Palak)
+author: John Snow Labs
+name: electra_qa_google_small_discriminator_squad
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `google_electra-small-discriminator_squad` is a English model originally trained by `Palak`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_google_small_discriminator_squad_en_5.2.0_3.0_1700124965933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_google_small_discriminator_squad_en_5.2.0_3.0_1700124965933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_google_small_discriminator_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_google_small_discriminator_squad","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.small.by_Palak").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_google_small_discriminator_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Palak/google_electra-small-discriminator_squad
\ No newline at end of file

From dded45fddc4359e5d2100633a77d84803a20c5ee Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 15:59:13 +0700
Subject: [PATCH 218/408] Add model
 2023-11-16-bert_qa_unqover_bert_base_uncased_newsqa_en

---
 ..._qa_unqover_bert_base_uncased_newsqa_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_bert_base_uncased_newsqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_bert_base_uncased_newsqa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_bert_base_uncased_newsqa_en.md
new file mode 100644
index 00000000000000..3d64943754d5aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_bert_base_uncased_newsqa_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from tli8hf)
+author: John Snow Labs
+name: bert_qa_unqover_bert_base_uncased_newsqa
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `unqover-bert-base-uncased-newsqa` is a English model orginally trained by `tli8hf`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_bert_base_uncased_newsqa_en_5.2.0_3.0_1700125145133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_bert_base_uncased_newsqa_en_5.2.0_3.0_1700125145133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_unqover_bert_base_uncased_newsqa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_unqover_bert_base_uncased_newsqa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.news.bert.base_uncased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_unqover_bert_base_uncased_newsqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/tli8hf/unqover-bert-base-uncased-newsqa
\ No newline at end of file

From abf8547504b2f4ad7b86150b405a789d7615d4ab Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 16:06:35 +0700
Subject: [PATCH 219/408] Add model
 2023-11-16-bert_qa_spanbert_base_finetuned_squad_r3f_en

---
 ...qa_spanbert_base_finetuned_squad_r3f_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_finetuned_squad_r3f_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_finetuned_squad_r3f_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_finetuned_squad_r3f_en.md
new file mode 100644
index 00000000000000..fa35314be944e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_finetuned_squad_r3f_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_finetuned_squad_r3f
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-finetuned-squad-r3f` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_finetuned_squad_r3f_en_5.2.0_3.0_1700125587369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_finetuned_squad_r3f_en_5.2.0_3.0_1700125587369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_finetuned_squad_r3f","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_finetuned_squad_r3f","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.base_finetuned").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_finetuned_squad_r3f|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|399.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-finetuned-squad-r3f
\ No newline at end of file

From 2e7959770288967e725316b6804656b65f4a39f9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:19:14 +0700
Subject: [PATCH 220/408] Add model
 2023-11-16-bert_qa_roberta_base_chinese_extractive_qa_scratch_zh

---
 ...a_base_chinese_extractive_qa_scratch_zh.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_roberta_base_chinese_extractive_qa_scratch_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_roberta_base_chinese_extractive_qa_scratch_zh.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_roberta_base_chinese_extractive_qa_scratch_zh.md
new file mode 100644
index 00000000000000..315d3b5a95849f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_roberta_base_chinese_extractive_qa_scratch_zh.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: Chinese BertForQuestionAnswering model (from jackh1995)
+author: John Snow Labs
+name: bert_qa_roberta_base_chinese_extractive_qa_scratch
+date: 2023-11-16
+tags: [zh, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-chinese-extractive-qa-scratch` is a Chinese model orginally trained by `jackh1995`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_chinese_extractive_qa_scratch_zh_5.2.0_3.0_1700140746123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_roberta_base_chinese_extractive_qa_scratch_zh_5.2.0_3.0_1700140746123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_roberta_base_chinese_extractive_qa_scratch","zh") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_roberta_base_chinese_extractive_qa_scratch","zh")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("zh.answer_question.bert.base.by_jackh1995").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_roberta_base_chinese_extractive_qa_scratch|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|zh|
+|Size:|407.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/jackh1995/roberta-base-chinese-extractive-qa-scratch
\ No newline at end of file

From 577fc871264ddc6edc4ef417a92ea9c18eb3bbba Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:20:13 +0700
Subject: [PATCH 221/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en

---
 ...ew_shot_k_128_finetuned_squad_seed_6_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en.md
new file mode 100644
index 00000000000000..f66381b6a99cdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-6` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en_5.2.0_3.0_1700140753164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6_en_5.2.0_3.0_1700140753164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_128d_seed_6").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|380.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-6
\ No newline at end of file

From 444f30b6bf1c1d0bc15835f7338d802a4a5e8c0a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:21:14 +0700
Subject: [PATCH 222/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en

---
 ...few_shot_k_16_finetuned_squad_seed_8_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..9934969c0232fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-8` is a English model originally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en_5.2.0_3.0_1700140756897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8_en_5.2.0_3.0_1700140756897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.squad.cased_seed_8_base_finetuned_few_shot").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|375.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-8
\ No newline at end of file

From 33c901026b3fe3b088d49cd53a6959f352ebb45a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:22:14 +0700
Subject: [PATCH 223/408] Add model
 2023-11-16-bert_qa_swahili_question_answer_latest_cased_sw

---
 ...swahili_question_answer_latest_cased_sw.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_swahili_question_answer_latest_cased_sw.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_swahili_question_answer_latest_cased_sw.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_swahili_question_answer_latest_cased_sw.md
new file mode 100644
index 00000000000000..6e8ac86534975b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_swahili_question_answer_latest_cased_sw.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: Swahili BertForQuestionAnswering Cased model (from innocent-charles)
+author: John Snow Labs
+name: bert_qa_swahili_question_answer_latest_cased
+date: 2023-11-16
+tags: [sw, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: sw
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `Swahili-question-answer-latest-cased` is a Swahili model originally trained by `innocent-charles`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_swahili_question_answer_latest_cased_sw_5.2.0_3.0_1700140782767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_swahili_question_answer_latest_cased_sw_5.2.0_3.0_1700140782767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_swahili_question_answer_latest_cased","sw")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_swahili_question_answer_latest_cased","sw")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_swahili_question_answer_latest_cased|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|sw|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/innocent-charles/Swahili-question-answer-latest-cased
+- https://github.com/Neurotech-HQ/Swahili-QA-dataset
+- https://blog.neurotech.africa/building-swahili-question-and-answering-with-haystack/
+- https://github.com/deepset-ai/haystack/
+- https://haystack.deepset.ai
+- https://www.linkedin.com/in/innocent-charles/
+- https://github.com/innocent-charles
+- https://paperswithcode.com/sota?task=Question+Answering&dataset=kenyacorpus
\ No newline at end of file

From 35404d0e910b48e8ecd7f3305bcc40ca6a0277cd Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:23:34 +0700
Subject: [PATCH 224/408] Add model
 2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en

---
 ..._768d_squad2_large_teacher_finetuned_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en.md
new file mode 100644
index 00000000000000..fb08ab3e0ae2a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from MichelBartels)
+author: John Snow Labs
+name: bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tinybert-6l-768d-squad2-large-teacher-finetuned` is a English model orginally trained by `MichelBartels`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en_5.2.0_3.0_1700141008040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned_en_5.2.0_3.0_1700141008040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.bert.large_tiny_768d.by_MichelBartels").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tinybert_6l_768d_squad2_large_teacher_finetuned|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|249.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/MichelBartels/tinybert-6l-768d-squad2-large-teacher-finetuned
\ No newline at end of file

From 77b6160664b1c56a2969f54a32d08015e11f0f90 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:24:34 +0700
Subject: [PATCH 225/408] Add model 2023-11-16-bert_qa_rule_softmatching_en

---
 ...2023-11-16-bert_qa_rule_softmatching_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_rule_softmatching_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_rule_softmatching_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_rule_softmatching_en.md
new file mode 100644
index 00000000000000..9f4ea5cb14a083
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_rule_softmatching_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from enoriega)
+author: John Snow Labs
+name: bert_qa_rule_softmatching
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `rule_softmatching` is a English model originally trained by `enoriega`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_rule_softmatching_en_5.2.0_3.0_1700141019762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_rule_softmatching_en_5.2.0_3.0_1700141019762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_rule_softmatching","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_rule_softmatching","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.by_enoriega").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_rule_softmatching|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/enoriega/rule_softmatching
\ No newline at end of file

From 39ef0829fea669833a02f181d72cdeb7641ab50f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:25:34 +0700
Subject: [PATCH 226/408] Add model
 2023-11-16-bert_qa_unqover_large_uncased_newsqa_en

---
 ...bert_qa_unqover_large_uncased_newsqa_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_large_uncased_newsqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_large_uncased_newsqa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_large_uncased_newsqa_en.md
new file mode 100644
index 00000000000000..5bed1f37730db2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_unqover_large_uncased_newsqa_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Large Uncased model (from tli8hf)
+author: John Snow Labs
+name: bert_qa_unqover_large_uncased_newsqa
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `unqover-bert-large-uncased-newsqa` is a English model originally trained by `tli8hf`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_large_uncased_newsqa_en_5.2.0_3.0_1700141035813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_unqover_large_uncased_newsqa_en_5.2.0_3.0_1700141035813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_unqover_large_uncased_newsqa","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_unqover_large_uncased_newsqa","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.news_sqa.uncased_large").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_unqover_large_uncased_newsqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/tli8hf/unqover-bert-large-uncased-newsqa
\ No newline at end of file

From 3b04ce2b90af3d5cafc3ec4be617a4ba47ddeaf2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:26:35 +0700
Subject: [PATCH 227/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en

---
 ...few_shot_k_32_finetuned_squad_seed_0_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en.md
new file mode 100644
index 00000000000000..c17c0dc9d35105
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-0` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en_5.2.0_3.0_1700141052019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0_en_5.2.0_3.0_1700141052019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_32d_seed_0").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_0|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|376.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-0
\ No newline at end of file

From e3058591f1ddf42d83efecaa6a3f4be1bff1df49 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:27:35 +0700
Subject: [PATCH 228/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en

---
 ...ew_shot_k_128_finetuned_squad_seed_8_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en.md
new file mode 100644
index 00000000000000..158339a3cf1f20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-8` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en_5.2.0_3.0_1700141048381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8_en_5.2.0_3.0_1700141048381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_128d_seed_8").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|380.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-128-finetuned-squad-seed-8
\ No newline at end of file

From fef2ebb4e14ffce2e5a7f3c4fee77daf847fc9bc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:28:35 +0700
Subject: [PATCH 229/408] Add model
 2023-11-16-bert_qa_sagemaker_bioclinicalbert_adr_en

---
 ...ert_qa_sagemaker_bioclinicalbert_adr_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_sagemaker_bioclinicalbert_adr_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sagemaker_bioclinicalbert_adr_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sagemaker_bioclinicalbert_adr_en.md
new file mode 100644
index 00000000000000..73f3fef1cd66f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_sagemaker_bioclinicalbert_adr_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English bert_qa_sagemaker_bioclinicalbert_adr BertForQuestionAnswering from anindabitm
+author: John Snow Labs
+name: bert_qa_sagemaker_bioclinicalbert_adr
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_sagemaker_bioclinicalbert_adr` is a English model originally trained by anindabitm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_sagemaker_bioclinicalbert_adr_en_5.2.0_3.0_1700141304291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_sagemaker_bioclinicalbert_adr_en_5.2.0_3.0_1700141304291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_sagemaker_bioclinicalbert_adr","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_sagemaker_bioclinicalbert_adr", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_sagemaker_bioclinicalbert_adr|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/anindabitm/sagemaker-BioclinicalBERT-ADR
\ No newline at end of file

From 2951f72909d020f0860c8e14214c92e00f73bd41 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:29:35 +0700
Subject: [PATCH 230/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en

---
 ...few_shot_k_64_finetuned_squad_seed_4_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en.md
new file mode 100644
index 00000000000000..4a851c7ad5fa0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-4` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en_5.2.0_3.0_1700141314824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4_en_5.2.0_3.0_1700141314824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_64d_seed_4").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_64_finetuned_squad_seed_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|378.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-64-finetuned-squad-seed-4
\ No newline at end of file

From f1d466c0d37ffbfb2bac88c35bfe10185c3342dc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:30:35 +0700
Subject: [PATCH 231/408] Add model 2023-11-16-bert_qa_tquad_base_turkish_tr

---
 ...023-11-16-bert_qa_tquad_base_turkish_tr.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tquad_base_turkish_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tquad_base_turkish_tr.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tquad_base_turkish_tr.md
new file mode 100644
index 00000000000000..b010c953e79b3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tquad_base_turkish_tr.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: Turkish BertForQuestionAnswering Base Cased model (from Izzet)
+author: John Snow Labs
+name: bert_qa_tquad_base_turkish
+date: 2023-11-16
+tags: [tr, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `qa_tquad_bert-base-turkish` is a Turkish model originally trained by `Izzet`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tquad_base_turkish_tr_5.2.0_3.0_1700141353029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tquad_base_turkish_tr_5.2.0_3.0_1700141353029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tquad_base_turkish","tr")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tquad_base_turkish","tr")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tquad_base_turkish|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|688.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Izzet/qa_tquad_bert-base-turkish
+- https://github.com/izzetkalic/botcuk-dataset-analyze/tree/main/datasets/qa-tquad
\ No newline at end of file

From 41a50b7d91864309a42966dbc56e96e6f11a5607 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:33:26 +0700
Subject: [PATCH 232/408] Add model
 2023-11-16-bert_qa_wskhanh_roberta_wwm_ext_large_zh

---
 ...ert_qa_wskhanh_roberta_wwm_ext_large_zh.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_wskhanh_roberta_wwm_ext_large_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_wskhanh_roberta_wwm_ext_large_zh.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_wskhanh_roberta_wwm_ext_large_zh.md
new file mode 100644
index 00000000000000..8ec3d0465397e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_wskhanh_roberta_wwm_ext_large_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese BertForQuestionAnswering Large Cased model (from wskhanh)
+author: John Snow Labs
+name: bert_qa_wskhanh_roberta_wwm_ext_large
+date: 2023-11-16
+tags: [zh, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `Roberta-wwm-ext-large-qa` is a Chinese model originally trained by `wskhanh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_wskhanh_roberta_wwm_ext_large_zh_5.2.0_3.0_1700141587605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_wskhanh_roberta_wwm_ext_large_zh_5.2.0_3.0_1700141587605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_wskhanh_roberta_wwm_ext_large","zh")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_wskhanh_roberta_wwm_ext_large","zh")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_wskhanh_roberta_wwm_ext_large|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|zh|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/wskhanh/Roberta-wwm-ext-large-qa
\ No newline at end of file

From cbe59899c97c88bc4237d8ab3052b75990f68464 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:34:26 +0700
Subject: [PATCH 233/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en

---
 ...rt_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md
index a33ab7bfaddcdd..b5ddcf11159998 100644
--- a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en.md
@@ -28,8 +28,8 @@ Pretrained Question Answering model, adapted from Hugging Face and curated to pr
 {:.btn-box}
 <button class="button button-orange" disabled>Live Demo</button>
 <button class="button button-orange" disabled>Open in Colab</button>
-[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_5.2.0_3.0_1700104318165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
-[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_5.2.0_3.0_1700104318165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_5.2.0_3.0_1700141625010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_6_en_5.2.0_3.0_1700141625010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
 
 ## How to use
 

From 101f6e5a3e759f73b4ca47eba537c53dd2ccb2c1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:35:27 +0700
Subject: [PATCH 234/408] Add model
 2023-11-16-bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en

---
 ...la_bert_base_uncased_finetuned_squad_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..fe5f03260b8b28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from victoraavila)
+author: John Snow Labs
+name: bert_qa_victoraavila_bert_base_uncased_finetuned_squad
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-finetuned-squad` is a English model orginally trained by `victoraavila`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700141658128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_victoraavila_bert_base_uncased_finetuned_squad_en_5.2.0_3.0_1700141658128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_victoraavila_bert_base_uncased_finetuned_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_victoraavila_bert_base_uncased_finetuned_squad","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.base_uncased.by_victoraavila").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_victoraavila_bert_base_uncased_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/victoraavila/bert-base-uncased-finetuned-squad
\ No newline at end of file

From 729bff1ed8b0bbf8b4698136a43ea1d728cd5ef7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:36:27 +0700
Subject: [PATCH 235/408] Add model 2023-11-16-bert_qa_spanbert_recruit_qa_en

---
 ...23-11-16-bert_qa_spanbert_recruit_qa_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_recruit_qa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_recruit_qa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_recruit_qa_en.md
new file mode 100644
index 00000000000000..38e9e252556f3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_recruit_qa_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from manishiitg)
+author: John Snow Labs
+name: bert_qa_spanbert_recruit_qa
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-recruit-qa` is a English model orginally trained by `manishiitg`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_recruit_qa_en_5.2.0_3.0_1700141653812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_recruit_qa_en_5.2.0_3.0_1700141653812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_recruit_qa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_recruit_qa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.by_manishiitg").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_recruit_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/manishiitg/spanbert-recruit-qa
\ No newline at end of file

From 67966c71eb0f377eb13ec9905dc9e210eb29e082 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:38:05 +0700
Subject: [PATCH 236/408] Add model
 2023-11-16-bert_qa_spanbert_large_recruit_qa_en

---
 ...16-bert_qa_spanbert_large_recruit_qa_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_large_recruit_qa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_large_recruit_qa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_large_recruit_qa_en.md
new file mode 100644
index 00000000000000..be0a31b5e8727f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_large_recruit_qa_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from manishiitg)
+author: John Snow Labs
+name: bert_qa_spanbert_large_recruit_qa
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-large-recruit-qa` is a English model orginally trained by `manishiitg`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_large_recruit_qa_en_5.2.0_3.0_1700141860561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_large_recruit_qa_en_5.2.0_3.0_1700141860561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_large_recruit_qa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_large_recruit_qa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.span_bert.large").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_large_recruit_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/manishiitg/spanbert-large-recruit-qa
\ No newline at end of file

From 908255822ee8f8440fb1b768fb6cfbe9766128f4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:39:05 +0700
Subject: [PATCH 237/408] Add model
 2023-11-16-bert_qa_youngjae_bert_finetuned_squad_accelerate_en

---
 ...gjae_bert_finetuned_squad_accelerate_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_youngjae_bert_finetuned_squad_accelerate_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_youngjae_bert_finetuned_squad_accelerate_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_youngjae_bert_finetuned_squad_accelerate_en.md
new file mode 100644
index 00000000000000..8b797adb88cf06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_youngjae_bert_finetuned_squad_accelerate_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from youngjae)
+author: John Snow Labs
+name: bert_qa_youngjae_bert_finetuned_squad_accelerate
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad-accelerate` is a English model orginally trained by `youngjae`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_youngjae_bert_finetuned_squad_accelerate_en_5.2.0_3.0_1700141918411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_youngjae_bert_finetuned_squad_accelerate_en_5.2.0_3.0_1700141918411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_youngjae_bert_finetuned_squad_accelerate","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_youngjae_bert_finetuned_squad_accelerate","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.accelerate.by_youngjae").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_youngjae_bert_finetuned_squad_accelerate|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/youngjae/bert-finetuned-squad-accelerate
\ No newline at end of file

From 9d8b926e4c05fa2d5e38a89ab1ff63e8af0af3e0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:40:05 +0700
Subject: [PATCH 238/408] Add model 2023-11-16-bert_qa_testpersianqa_fa

---
 .../2023-11-16-bert_qa_testpersianqa_fa.md    | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_testpersianqa_fa.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_testpersianqa_fa.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_testpersianqa_fa.md
new file mode 100644
index 00000000000000..f5ee7ac0552855
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_testpersianqa_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian BertForQuestionAnswering Cased model (from AlirezaBaneshi)
+author: John Snow Labs
+name: bert_qa_testpersianqa
+date: 2023-11-16
+tags: [fa, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `testPersianQA` is a Persian model originally trained by `AlirezaBaneshi`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_testpersianqa_fa_5.2.0_3.0_1700141974295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_testpersianqa_fa_5.2.0_3.0_1700141974295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_testpersianqa","fa") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["اسم من چیست؟", "نام من کلارا است و من در برکلی زندگی می کنم."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_testpersianqa","fa") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("اسم من چیست؟", "نام من کلارا است و من در برکلی زندگی می کنم.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_testpersianqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|606.5 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/AlirezaBaneshi/testPersianQA
\ No newline at end of file

From 573c70109358363ab22963b0596f8588c7a3ea7e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:41:05 +0700
Subject: [PATCH 239/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en

---
 ...ew_shot_k_16_finetuned_squad_seed_42_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en.md
new file mode 100644
index 00000000000000..9f9936343e79c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-42` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en_5.2.0_3.0_1700141920271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42_en_5.2.0_3.0_1700141920271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_seed_42").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_42|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|380.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-16-finetuned-squad-seed-42
\ No newline at end of file

From 4856c6bc22b79d971a93cc205104704c2cb37fd7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:43:57 +0700
Subject: [PATCH 240/408] Add model 2023-11-16-electra_qa_biom_large_squad2_en

---
 ...3-11-16-electra_qa_biom_large_squad2_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_en.md
new file mode 100644
index 00000000000000..b89a68215a818d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English electra_qa_biom_large_squad2 BertForQuestionAnswering from sultan
+author: John Snow Labs
+name: electra_qa_biom_large_squad2
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_biom_large_squad2` is a English model originally trained by sultan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_biom_large_squad2_en_5.2.0_3.0_1700142216874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_biom_large_squad2_en_5.2.0_3.0_1700142216874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_biom_large_squad2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_biom_large_squad2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_biom_large_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/sultan/BioM-ELECTRA-Large-SQuAD2
\ No newline at end of file

From ecbfa7e96481a2496cc55ade3df69e275fc6a444 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:44:58 +0700
Subject: [PATCH 241/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en

---
 ...few_shot_k_32_finetuned_squad_seed_2_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en.md
new file mode 100644
index 00000000000000..5e203a207a3a36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-2` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en_5.2.0_3.0_1700142255782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2_en_5.2.0_3.0_1700142255782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_32d_seed_2").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_32_finetuned_squad_seed_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|376.3 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-2
\ No newline at end of file

From 8847f23c51ea1e485fc5a9cf370f97d06a6382d9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:45:58 +0700
Subject: [PATCH 242/408] Add model 2023-11-16-bert_qa_ytu_base_turkish_tr

---
 .../2023-11-16-bert_qa_ytu_base_turkish_tr.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_ytu_base_turkish_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_ytu_base_turkish_tr.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_ytu_base_turkish_tr.md
new file mode 100644
index 00000000000000..44e901f9ee7094
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_ytu_base_turkish_tr.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: Turkish BertForQuestionAnswering Base Cased model (from Izzet)
+author: John Snow Labs
+name: bert_qa_ytu_base_turkish
+date: 2023-11-16
+tags: [tr, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `qa_ytu_bert-base-turkish` is a Turkish model originally trained by `Izzet`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_ytu_base_turkish_tr_5.2.0_3.0_1700142270831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_ytu_base_turkish_tr_5.2.0_3.0_1700142270831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ytu_base_turkish","tr")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ytu_base_turkish","tr")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_ytu_base_turkish|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|688.9 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Izzet/qa_ytu_bert-base-turkish
+- https://github.com/izzetkalic/botcuk-dataset-analyze/tree/main/datasets/qa-ytu
\ No newline at end of file

From 818741c81c79432579565459ac4a334a790b7f9a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:46:58 +0700
Subject: [PATCH 243/408] Add model
 2023-11-16-bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th

---
 ...ed_finetuned_xquadv1_finetuned_squad_th.md | 109 ++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th.md
new file mode 100644
index 00000000000000..35c224af24a251
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th.md
@@ -0,0 +1,109 @@
+---
+layout: model
+title: Thai BertForQuestionAnswering model (from wicharnkeisei)
+author: John Snow Labs
+name: bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad
+date: 2023-11-16
+tags: [th, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: th
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `thai-bert-multi-cased-finetuned-xquadv1-finetuned-squad` is a Thai model orginally trained by `wicharnkeisei`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th_5.2.0_3.0_1700142277018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad_th_5.2.0_3.0_1700142277018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad","th") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad","th")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("th.answer_question.xquad_squad.bert.cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_thai_bert_multi_cased_finetuned_xquadv1_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|th|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/wicharnkeisei/thai-bert-multi-cased-finetuned-xquadv1-finetuned-squad
+- https://github.com/iapp-technology/iapp-wiki-qa-dataset
\ No newline at end of file

From 1685bdc7ec42bee0ee444d3a5e5b74ade7a1285e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:50:53 +0700
Subject: [PATCH 244/408] Add model
 2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en

---
 ...w_shot_k_512_finetuned_squad_seed_10_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en.md
new file mode 100644
index 00000000000000..93d3071181b47e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from anas-awadalla)
+author: John Snow Labs
+name: bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-10` is a English model orginally trained by `anas-awadalla`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en_5.2.0_3.0_1700142645727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10_en_5.2.0_3.0_1700142645727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.span_bert.base_cased_512d_seed_10").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|386.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/anas-awadalla/spanbert-base-cased-few-shot-k-512-finetuned-squad-seed-10
\ No newline at end of file

From 85af7b19dacd374fe1317c4ca64be86fb34fa568 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:51:53 +0700
Subject: [PATCH 245/408] Add model
 2023-11-16-bert_qa_tests_finetuned_squad_test_bert_en

---
 ...t_qa_tests_finetuned_squad_test_bert_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tests_finetuned_squad_test_bert_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tests_finetuned_squad_test_bert_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tests_finetuned_squad_test_bert_en.md
new file mode 100644
index 00000000000000..025bc4be174cfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tests_finetuned_squad_test_bert_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from ruselkomp)
+author: John Snow Labs
+name: bert_qa_tests_finetuned_squad_test_bert
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tests-finetuned-squad-test-bert` is a English model orginally trained by `ruselkomp`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tests_finetuned_squad_test_bert_en_5.2.0_3.0_1700142647414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tests_finetuned_squad_test_bert_en_5.2.0_3.0_1700142647414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tests_finetuned_squad_test_bert","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_tests_finetuned_squad_test_bert","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.bert.by_ruselkomp").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tests_finetuned_squad_test_bert|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.6 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ruselkomp/tests-finetuned-squad-test-bert
\ No newline at end of file

From 9d553c84cd4cf4fcf811c8bcdcd02397c07a5431 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:52:53 +0700
Subject: [PATCH 246/408] Add model 2023-11-16-bert_qa_zero_shot_en

---
 .../2023-11-16-bert_qa_zero_shot_en.md        | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_zero_shot_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_zero_shot_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_zero_shot_en.md
new file mode 100644
index 00000000000000..cf1ff755b936bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_zero_shot_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from krinal214)
+author: John Snow Labs
+name: bert_qa_zero_shot
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `zero_shot` is a English model orginally trained by `krinal214`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_zero_shot_en_5.2.0_3.0_1700142728982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_zero_shot_en_5.2.0_3.0_1700142728982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_zero_shot","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_zero_shot","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.zero_shot.by_krinal214").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_zero_shot|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/krinal214/zero_shot
\ No newline at end of file

From f7ad35e9adbf3b77cb90bbacbad67ac63625151b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 20:57:52 +0700
Subject: [PATCH 247/408] Add model
 2023-11-16-electra_qa_biom_large_squad2_bioasq8b_en

---
 ...lectra_qa_biom_large_squad2_bioasq8b_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_bioasq8b_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_bioasq8b_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_bioasq8b_en.md
new file mode 100644
index 00000000000000..016378d6813c5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biom_large_squad2_bioasq8b_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English electra_qa_biom_large_squad2_bioasq8b BertForQuestionAnswering from sultan
+author: John Snow Labs
+name: electra_qa_biom_large_squad2_bioasq8b
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_biom_large_squad2_bioasq8b` is a English model originally trained by sultan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_biom_large_squad2_bioasq8b_en_5.2.0_3.0_1700143012944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_biom_large_squad2_bioasq8b_en_5.2.0_3.0_1700143012944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_biom_large_squad2_bioasq8b","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_biom_large_squad2_bioasq8b", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_biom_large_squad2_bioasq8b|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/sultan/BioM-ELECTRA-Large-SQuAD2-BioASQ8B
\ No newline at end of file

From f612a1d6ba62ab5b54ce0fe5f705d49fee93a231 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 21:03:00 +0700
Subject: [PATCH 248/408] Add model
 2023-11-16-electra_qa_dspfirst_finetuning_4_en

---
 ...-16-electra_qa_dspfirst_finetuning_4_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_dspfirst_finetuning_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_dspfirst_finetuning_4_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_dspfirst_finetuning_4_en.md
new file mode 100644
index 00000000000000..9e1a9a2facdfbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_dspfirst_finetuning_4_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English electra_qa_dspfirst_finetuning_4 BertForQuestionAnswering from ptran74
+author: John Snow Labs
+name: electra_qa_dspfirst_finetuning_4
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_dspfirst_finetuning_4` is a English model originally trained by ptran74.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_dspfirst_finetuning_4_en_5.2.0_3.0_1700143360634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_dspfirst_finetuning_4_en_5.2.0_3.0_1700143360634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_dspfirst_finetuning_4","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_dspfirst_finetuning_4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_dspfirst_finetuning_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/ptran74/DSPFirst-Finetuning-4
\ No newline at end of file

From 86402e507a5451cfeecb4462f8a373a7a16e12ba Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:21:24 +0700
Subject: [PATCH 249/408] Add model 2023-11-16-matbert_finetuned_squad_en

---
 .../2023-11-16-matbert_finetuned_squad_en.md  | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-matbert_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-matbert_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-matbert_finetuned_squad_en.md
new file mode 100644
index 00000000000000..1382b38ea23e1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-matbert_finetuned_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English matbert_finetuned_squad BertForQuestionAnswering from HongyangLi
+author: John Snow Labs
+name: matbert_finetuned_squad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`matbert_finetuned_squad` is a English model originally trained by HongyangLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/matbert_finetuned_squad_en_5.2.0_3.0_1700151674563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/matbert_finetuned_squad_en_5.2.0_3.0_1700151674563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("matbert_finetuned_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("matbert_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|matbert_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/HongyangLi/Matbert-finetuned-squad
\ No newline at end of file

From ebcdf17653cfdb8e728a2796435fe93e12104c28 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:29:13 +0700
Subject: [PATCH 250/408] Add model
 2023-11-16-bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en

---
 ...l_l12_h384_uncased_natural_questions_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en.md
new file mode 100644
index 00000000000000..70d477ca39bfc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from nyorain)
+author: John Snow Labs
+name: bert_qa_xtremedistil_l12_h384_uncased_natural_questions
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l12-h384-uncased-natural-questions` is a English model originally trained by `nyorain`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en_5.2.0_3.0_1700152150227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l12_h384_uncased_natural_questions_en_5.2.0_3.0_1700152150227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l12_h384_uncased_natural_questions","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l12_h384_uncased_natural_questions","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l12_h384_uncased_natural_questions|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|124.1 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/nyorain/xtremedistil-l12-h384-uncased-natural-questions
\ No newline at end of file

From 6e65d15fe9300ed87bc7792e4d7b28f9d600f29c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:30:46 +0700
Subject: [PATCH 251/408] Add model
 2023-11-16-electra_qa_hankzhong_small_discriminator_finetuned_squad_en

---
 ..._small_discriminator_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_hankzhong_small_discriminator_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_hankzhong_small_discriminator_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_hankzhong_small_discriminator_finetuned_squad_en.md
new file mode 100644
index 00000000000000..897c5fab4d1cbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_hankzhong_small_discriminator_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from hankzhong)
+author: John Snow Labs
+name: electra_qa_hankzhong_small_discriminator_finetuned_squad
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-small-discriminator-finetuned-squad` is a English model originally trained by `hankzhong`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_hankzhong_small_discriminator_finetuned_squad_en_5.2.0_3.0_1700152242588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_hankzhong_small_discriminator_finetuned_squad_en_5.2.0_3.0_1700152242588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_hankzhong_small_discriminator_finetuned_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_hankzhong_small_discriminator_finetuned_squad","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.small.by_hankzhong").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_hankzhong_small_discriminator_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/hankzhong/electra-small-discriminator-finetuned-squad
\ No newline at end of file

From 4401aaf367d6cee13ac13c84c2d22f073469b0c3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:46:49 +0700
Subject: [PATCH 252/408] Add model
 2023-11-16-bert_base_multilingual_uncased_finetuned_squadv2_xx

---
 ...ltilingual_uncased_finetuned_squadv2_xx.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_uncased_finetuned_squadv2_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_uncased_finetuned_squadv2_xx.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_uncased_finetuned_squadv2_xx.md
new file mode 100644
index 00000000000000..330c2786f812d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_uncased_finetuned_squadv2_xx.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_uncased_finetuned_squadv2 BertForQuestionAnswering from monakth
+author: John Snow Labs
+name: bert_base_multilingual_uncased_finetuned_squadv2
+date: 2023-11-16
+tags: [bert, xx, open_source, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_finetuned_squadv2` is a Multilingual model originally trained by monakth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_squadv2_xx_5.2.0_3.0_1700153197666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_squadv2_xx_5.2.0_3.0_1700153197666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_uncased_finetuned_squadv2","xx") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_multilingual_uncased_finetuned_squadv2", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_uncased_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/monakth/bert-base-multilingual-uncased-finetuned-squadv2
\ No newline at end of file

From 5414949b551663dc87e866e06bed06349da88b24 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:48:13 +0700
Subject: [PATCH 253/408] Add model
 2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en

---
 ..._uncased_finetuned_lr_2e_05_epochs_6_en.md | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en.md
new file mode 100644
index 00000000000000..995999d0a17412
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en.md
@@ -0,0 +1,108 @@
+---
+layout: model
+title: English BertForQuestionAnswering model (from husnu)
+author: John Snow Labs
+name: bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6
+date: 2023-11-16
+tags: [en, open_source, question_answering, bert, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l6-h256-uncased-finetuned_lr-2e-05_epochs-6` is a English model orginally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en_5.2.0_3.0_1700153291634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6_en_5.2.0_3.0_1700153291634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = BertForQuestionAnswering
+.pretrained("bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.xtremedistiled_uncased_lr_2e_05_epochs_6.by_husnu").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l6_h256_uncased_finetuned_lr_2e_05_epochs_6|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|47.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/xtremedistil-l6-h256-uncased-finetuned_lr-2e-05_epochs-6
\ No newline at end of file

From d9efee3e099b055938ad03608463dba0f37cf614 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:54:19 +0700
Subject: [PATCH 254/408] Add model 2023-11-16-indobert_squad_en

---
 .../2023-11-16-indobert_squad_en.md           | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-indobert_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-indobert_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-indobert_squad_en.md
new file mode 100644
index 00000000000000..51b85e3c6a5961
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-indobert_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English indobert_squad BertForQuestionAnswering from esakrissa
+author: John Snow Labs
+name: indobert_squad
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_squad` is a English model originally trained by esakrissa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_squad_en_5.2.0_3.0_1700153650731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_squad_en_5.2.0_3.0_1700153650731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("indobert_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("indobert_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/esakrissa/IndoBERT-SQuAD
\ No newline at end of file

From 10b502885c19f2e5d9d5397622a9587771faa7dc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Thu, 16 Nov 2023 23:56:57 +0700
Subject: [PATCH 255/408] Add model 2023-11-16-bert_qa_test02_en

---
 .../2023-11-16-bert_qa_test02_en.md           | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_test02_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_test02_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_test02_en.md
new file mode 100644
index 00000000000000..c3726256f1f1dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_test02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from Akert)
+author: John Snow Labs
+name: bert_qa_test02
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `test02` is a English model originally trained by `Akert`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_test02_en_5.2.0_3.0_1700153810019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_test02_en_5.2.0_3.0_1700153810019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_test02","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_test02","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_test02|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Akert/test02
\ No newline at end of file

From b7962a0e9f6c59fa2df4b3d21136256fac2e8fa2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:02:19 +0700
Subject: [PATCH 256/408] Add model 2023-11-16-bert_large_mpdocvqa_en

---
 .../2023-11-16-bert_large_mpdocvqa_en.md      | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_large_mpdocvqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_large_mpdocvqa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_large_mpdocvqa_en.md
new file mode 100644
index 00000000000000..6e89062dad12aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_large_mpdocvqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_large_mpdocvqa BertForQuestionAnswering from rubentito
+author: John Snow Labs
+name: bert_large_mpdocvqa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mpdocvqa` is a English model originally trained by rubentito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mpdocvqa_en_5.2.0_3.0_1700154120764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mpdocvqa_en_5.2.0_3.0_1700154120764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_mpdocvqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_large_mpdocvqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_mpdocvqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rubentito/bert-large-mpdocvqa
\ No newline at end of file

From 03af373d758924e506142a20e883e5f76ff797b1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:05:39 +0700
Subject: [PATCH 257/408] Add model
 2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en

---
 ...ed_tquad_finetuned_lr_2e_05_epochs_3_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en.md
new file mode 100644
index 00000000000000..09792763ffb703
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from husnu)
+author: John Snow Labs
+name: bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l6-h256-uncased-TQUAD-finetuned_lr-2e-05_epochs-3` is a English model originally trained by `husnu`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en_5.2.0_3.0_1700154318451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3_en_5.2.0_3.0_1700154318451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.tquad.xtremedistiled_uncased_finetuned_epochs_3").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|47.3 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/husnu/xtremedistil-l6-h256-uncased-TQUAD-finetuned_lr-2e-05_epochs-3
\ No newline at end of file

From 9e01f610f77f43c08db3bd63e724c60e36c26e42 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:13:08 +0700
Subject: [PATCH 258/408] Add model
 2023-11-16-bert_base_multilingual_cased_finetuned_squad_jensh_xx

---
 ...ilingual_cased_finetuned_squad_jensh_xx.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_cased_finetuned_squad_jensh_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_cased_finetuned_squad_jensh_xx.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_cased_finetuned_squad_jensh_xx.md
new file mode 100644
index 00000000000000..b4f01ccba84b31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_multilingual_cased_finetuned_squad_jensh_xx.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned_squad_jensh BertForQuestionAnswering from JensH
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned_squad_jensh
+date: 2023-11-16
+tags: [bert, xx, open_source, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_squad_jensh` is a Multilingual model originally trained by JensH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_squad_jensh_xx_5.2.0_3.0_1700154777207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_squad_jensh_xx_5.2.0_3.0_1700154777207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_cased_finetuned_squad_jensh","xx") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_multilingual_cased_finetuned_squad_jensh", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned_squad_jensh|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/JensH/bert-base-multilingual-cased-finetuned-squad
\ No newline at end of file

From 5a1f8a24ae0fffedb6fc4790612afb17fce22770 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:14:36 +0700
Subject: [PATCH 259/408] Add model
 2023-11-16-bert_qa_tiny_finetuned_squadv2_en

---
 ...11-16-bert_qa_tiny_finetuned_squadv2_en.md | 102 ++++++++++++++++++
 1 file changed, 102 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_squadv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..ccd6a3beb073aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tiny_finetuned_squadv2_en.md
@@ -0,0 +1,102 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny Cased model (from M-FAC)
+author: John Snow Labs
+name: bert_qa_tiny_finetuned_squadv2
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-tiny-finetuned-squadv2` is a English model originally trained by `M-FAC`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_finetuned_squadv2_en_5.2.0_3.0_1700154874575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tiny_finetuned_squadv2_en_5.2.0_3.0_1700154874575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tiny_finetuned_squadv2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_tiny_finetuned_squadv2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2.v2_tiny_finetuned").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tiny_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/M-FAC/bert-tiny-finetuned-squadv2
+- https://arxiv.org/pdf/2107.03356.pdf
+- https://github.com/IST-DASLab/M-FAC
\ No newline at end of file

From 26981a6c055e8044bafb04b2b04a991db2e73a28 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:15:36 +0700
Subject: [PATCH 260/408] Add model 2023-11-16-qthang_finetuned_en

---
 .../2023-11-16-qthang_finetuned_en.md         | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-qthang_finetuned_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-qthang_finetuned_en.md b/docs/_posts/ahmedlone127/2023-11-16-qthang_finetuned_en.md
new file mode 100644
index 00000000000000..5d02f29121b2f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-qthang_finetuned_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English qthang_finetuned BertForQuestionAnswering from ThangDinh
+author: John Snow Labs
+name: qthang_finetuned
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qthang_finetuned` is a English model originally trained by ThangDinh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qthang_finetuned_en_5.2.0_3.0_1700154874434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qthang_finetuned_en_5.2.0_3.0_1700154874434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qthang_finetuned","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("qthang_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qthang_finetuned|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/ThangDinh/qthang-finetuned
\ No newline at end of file

From 5092bea27cf894001f0cdf5de943b5b648cc1c05 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:16:36 +0700
Subject: [PATCH 261/408] Add model
 2023-11-16-bert_qa_ydshieh_tiny_random_forquestionanswering_ja

---
 ...ieh_tiny_random_forquestionanswering_ja.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_ydshieh_tiny_random_forquestionanswering_ja.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_ydshieh_tiny_random_forquestionanswering_ja.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_ydshieh_tiny_random_forquestionanswering_ja.md
new file mode 100644
index 00000000000000..b072aee0c0cbbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_ydshieh_tiny_random_forquestionanswering_ja.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Japanese BertForQuestionAnswering Tiny Cased model (from ydshieh)
+author: John Snow Labs
+name: bert_qa_ydshieh_tiny_random_forquestionanswering
+date: 2023-11-16
+tags: [ja, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: ja
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tiny-random-BertForQuestionAnswering` is a Japanese model originally trained by `ydshieh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_ydshieh_tiny_random_forquestionanswering_ja_5.2.0_3.0_1700154938859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_ydshieh_tiny_random_forquestionanswering_ja_5.2.0_3.0_1700154938859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ydshieh_tiny_random_forquestionanswering","ja")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_ydshieh_tiny_random_forquestionanswering","ja")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_ydshieh_tiny_random_forquestionanswering|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ja|
+|Size:|346.5 KB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ydshieh/tiny-random-BertForQuestionAnswering
\ No newline at end of file

From 80e783b7d01b3b4177c998c7e4d27e361d4668a9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:27:25 +0700
Subject: [PATCH 262/408] Add model 2023-11-16-wspalign_mbert_base_xx

---
 .../2023-11-16-wspalign_mbert_base_xx.md      | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-wspalign_mbert_base_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-wspalign_mbert_base_xx.md b/docs/_posts/ahmedlone127/2023-11-16-wspalign_mbert_base_xx.md
new file mode 100644
index 00000000000000..0ad8337dac86a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-wspalign_mbert_base_xx.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Multilingual wspalign_mbert_base BertForQuestionAnswering from qiyuw
+author: John Snow Labs
+name: wspalign_mbert_base
+date: 2023-11-16
+tags: [bert, xx, open_source, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wspalign_mbert_base` is a Multilingual model originally trained by qiyuw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wspalign_mbert_base_xx_5.2.0_3.0_1700155632305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wspalign_mbert_base_xx_5.2.0_3.0_1700155632305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("wspalign_mbert_base","xx") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("wspalign_mbert_base", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wspalign_mbert_base|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/qiyuw/WSPAlign-mbert-base
\ No newline at end of file

From 27e518e8c11aa15cdb0fbfe281389777a75d9266 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:35:44 +0700
Subject: [PATCH 263/408] Add model 2023-11-16-bert_test_model_en

---
 .../2023-11-16-bert_test_model_en.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_test_model_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_test_model_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_test_model_en.md
new file mode 100644
index 00000000000000..00700f747baca2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_test_model_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_test_model BertForQuestionAnswering from Jellevdl
+author: John Snow Labs
+name: bert_test_model
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_test_model` is a English model originally trained by Jellevdl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_test_model_en_5.2.0_3.0_1700156136455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_test_model_en_5.2.0_3.0_1700156136455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_test_model","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_test_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_test_model|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Jellevdl/Bert-test-model
\ No newline at end of file

From 6918214121ddb14b720c981cd3a8c2086b357008 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:41:20 +0700
Subject: [PATCH 264/408] Add model 2023-11-16-costa_rica_cased_qa_en

---
 .../2023-11-16-costa_rica_cased_qa_en.md      | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-costa_rica_cased_qa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-costa_rica_cased_qa_en.md b/docs/_posts/ahmedlone127/2023-11-16-costa_rica_cased_qa_en.md
new file mode 100644
index 00000000000000..f59c1c8f661478
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-costa_rica_cased_qa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English costa_rica_cased_qa BertForQuestionAnswering from nymiz
+author: John Snow Labs
+name: costa_rica_cased_qa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`costa_rica_cased_qa` is a English model originally trained by nymiz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/costa_rica_cased_qa_en_5.2.0_3.0_1700156398909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/costa_rica_cased_qa_en_5.2.0_3.0_1700156398909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("costa_rica_cased_qa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("costa_rica_cased_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|costa_rica_cased_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/nymiz/costa-rica_cased-QA
\ No newline at end of file

From c9eb8495ec30c7fb4e9218152d77aa3157407359 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:43:17 +0700
Subject: [PATCH 265/408] Add model
 2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en

---
 ...t_6l_768d_squad2_large_teacher_dummy_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en.md
new file mode 100644
index 00000000000000..4635ddf462cc0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Tiny Cased model (from MichelBartels)
+author: John Snow Labs
+name: bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tinybert-6l-768d-squad2-large-teacher-dummy` is a English model originally trained by `MichelBartels`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en_5.2.0_3.0_1700156590757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy_en_5.2.0_3.0_1700156590757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2.large_tiny_768d.by_MichelBartels").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tinybert_6l_768d_squad2_large_teacher_dummy|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|248.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/MichelBartels/tinybert-6l-768d-squad2-large-teacher-dummy
\ No newline at end of file

From 842ab444288967d7fe96ab6fdc225aa04b76afc2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 00:44:17 +0700
Subject: [PATCH 266/408] Add model
 2023-11-16-bert_qa_yossra_finetuned_squad_en

---
 ...11-16-bert_qa_yossra_finetuned_squad_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_yossra_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_yossra_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_yossra_finetuned_squad_en.md
new file mode 100644
index 00000000000000..cc04a3a6a65d2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_yossra_finetuned_squad_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from yossra)
+author: John Snow Labs
+name: bert_qa_yossra_finetuned_squad
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `yossra`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_yossra_finetuned_squad_en_5.2.0_3.0_1700156597353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_yossra_finetuned_squad_en_5.2.0_3.0_1700156597353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_yossra_finetuned_squad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_yossra_finetuned_squad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squad.finetuned.by_yossra").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_yossra_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/yossra/bert-finetuned-squad
\ No newline at end of file

From 3f5dfd8da0a6934a03e704953c0959d559b250d6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 01:00:15 +0700
Subject: [PATCH 267/408] Add model 2023-11-16-bert_squad_covidqa_2_en

---
 .../2023-11-16-bert_squad_covidqa_2_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_squad_covidqa_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_squad_covidqa_2_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_squad_covidqa_2_en.md
new file mode 100644
index 00000000000000..c36a6337fd01b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_squad_covidqa_2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_squad_covidqa_2 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_squad_covidqa_2
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_covidqa_2` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_covidqa_2_en_5.2.0_3.0_1700157604047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_covidqa_2_en_5.2.0_3.0_1700157604047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_squad_covidqa_2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_squad_covidqa_2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_covidqa_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-squad-covidqa-2
\ No newline at end of file

From f0461b8b37a9276d7b41970bd56a9133e96e9d88 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 01:11:33 +0700
Subject: [PATCH 268/408] Add model 2023-11-16-mbert_squad_en

---
 .../ahmedlone127/2023-11-16-mbert_squad_en.md | 92 +++++++++++++++++++
 1 file changed, 92 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-mbert_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-mbert_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-mbert_squad_en.md
new file mode 100644
index 00000000000000..9f188f786772fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-mbert_squad_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English mbert_squad BertEmbeddings from oceanpty
+author: John Snow Labs
+name: mbert_squad
+date: 2023-11-16
+tags: [bert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_squad` is a English model originally trained by oceanpty.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_squad_en_5.2.0_3.0_1700158280562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_squad_en_5.2.0_3.0_1700158280562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("mbert_squad","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("mbert_squad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/oceanpty/mbert-squad
\ No newline at end of file

From 3d494b38466cfa7f2bcd8fb461f018db3366eff6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 01:12:33 +0700
Subject: [PATCH 269/408] Add model 2023-11-16-chatanswering_ptbr_pt

---
 .../2023-11-16-chatanswering_ptbr_pt.md       | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-chatanswering_ptbr_pt.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-chatanswering_ptbr_pt.md b/docs/_posts/ahmedlone127/2023-11-16-chatanswering_ptbr_pt.md
new file mode 100644
index 00000000000000..e8f9686b60a5e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-chatanswering_ptbr_pt.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Portuguese chatanswering_ptbr BertForQuestionAnswering from JeanL-0
+author: John Snow Labs
+name: chatanswering_ptbr
+date: 2023-11-16
+tags: [bert, pt, open_source, question_answering, onnx]
+task: Question Answering
+language: pt
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatanswering_ptbr` is a Portuguese model originally trained by JeanL-0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatanswering_ptbr_pt_5.2.0_3.0_1700158279659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatanswering_ptbr_pt_5.2.0_3.0_1700158279659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("chatanswering_ptbr","pt") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("chatanswering_ptbr", "pt")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatanswering_ptbr|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|pt|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/JeanL-0/ChatAnswering-PTBR
\ No newline at end of file

From 19a15090c221cf96dc2390e2d2fc200848fb6b6c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 01:14:03 +0700
Subject: [PATCH 270/408] Add model
 2023-11-16-bert_qa_tmgondal_finetuned_squad_en

---
 ...-16-bert_qa_tmgondal_finetuned_squad_en.md | 94 +++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_tmgondal_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tmgondal_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tmgondal_finetuned_squad_en.md
new file mode 100644
index 00000000000000..7096a557a96513
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_tmgondal_finetuned_squad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from tmgondal)
+author: John Snow Labs
+name: bert_qa_tmgondal_finetuned_squad
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-squad` is a English model originally trained by `tmgondal`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_tmgondal_finetuned_squad_en_5.2.0_3.0_1700158435973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_tmgondal_finetuned_squad_en_5.2.0_3.0_1700158435973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tmgondal_finetuned_squad","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_tmgondal_finetuned_squad","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_tmgondal_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/tmgondal/bert-finetuned-squad
\ No newline at end of file

From c2037abb5337ce1a36779b52a61e5928da2a38a6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 01:42:26 +0700
Subject: [PATCH 271/408] Add model
 2023-11-16-bert_italian_cased_question_answering_it

---
 ...ert_italian_cased_question_answering_it.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_italian_cased_question_answering_it.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_italian_cased_question_answering_it.md b/docs/_posts/ahmedlone127/2023-11-16-bert_italian_cased_question_answering_it.md
new file mode 100644
index 00000000000000..41214d4bf8fd96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_italian_cased_question_answering_it.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Italian bert_italian_cased_question_answering BertForQuestionAnswering from osiria
+author: John Snow Labs
+name: bert_italian_cased_question_answering
+date: 2023-11-16
+tags: [bert, it, open_source, question_answering, onnx]
+task: Question Answering
+language: it
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_cased_question_answering` is a Italian model originally trained by osiria.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_cased_question_answering_it_5.2.0_3.0_1700160138104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_cased_question_answering_it_5.2.0_3.0_1700160138104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_italian_cased_question_answering","it") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_italian_cased_question_answering", "it")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_italian_cased_question_answering|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|it|
+|Size:|409.0 MB|
+
+## References
+
+https://huggingface.co/osiria/bert-italian-cased-question-answering
\ No newline at end of file

From e59655232ff595c807829975a4d16e5946fc32a7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:05:30 +0700
Subject: [PATCH 272/408] Add model
 2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en

---
 ...d_l_2_h_128_a_2_cord19_200616_squad2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en.md
new file mode 100644
index 00000000000000..febda140d054f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-2_H-128_A-2_cord19-200616_squad2` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en_5.2.0_3.0_1700161528646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2_en_5.2.0_3.0_1700161528646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2_cord19.uncased_2l_128d_a2a_128d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_2_h_128_a_2_cord19_200616_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.6 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-2_H-128_A-2_cord19-200616_squad2
\ No newline at end of file

From 865c2181ac4e01a49f4d32a823b3f7b59b27ea12 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:10:07 +0700
Subject: [PATCH 273/408] Add model 2023-11-16-ntu_adl_span_selection_bert_en

---
 ...23-11-16-ntu_adl_span_selection_bert_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_bert_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_bert_en.md b/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_bert_en.md
new file mode 100644
index 00000000000000..f6ab6624614dfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_bert_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English ntu_adl_span_selection_bert BertForQuestionAnswering from xjlulu
+author: John Snow Labs
+name: ntu_adl_span_selection_bert
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ntu_adl_span_selection_bert` is a English model originally trained by xjlulu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_bert_en_5.2.0_3.0_1700161797686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_bert_en_5.2.0_3.0_1700161797686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ntu_adl_span_selection_bert","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ntu_adl_span_selection_bert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ntu_adl_span_selection_bert|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.1 MB|
+
+## References
+
+https://huggingface.co/xjlulu/ntu_adl_span_selection_bert
\ No newline at end of file

From 4c53e05bdcb4cba3c19ea3752392e136ee94b26f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:11:08 +0700
Subject: [PATCH 274/408] Add model
 2023-11-16-bert_finetuned_squad_salmonai123_en

---
 ...-16-bert_finetuned_squad_salmonai123_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_salmonai123_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_salmonai123_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_salmonai123_en.md
new file mode 100644
index 00000000000000..2fc81554205d6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_salmonai123_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_salmonai123 BertForQuestionAnswering from SalmonAI123
+author: John Snow Labs
+name: bert_finetuned_squad_salmonai123
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_salmonai123` is a English model originally trained by SalmonAI123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_salmonai123_en_5.2.0_3.0_1700161797677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_salmonai123_en_5.2.0_3.0_1700161797677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_salmonai123","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_salmonai123", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_salmonai123|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/SalmonAI123/bert-finetuned-squad
\ No newline at end of file

From 799ac7122cc05911135042cba2aa1b6568fd0e03 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:12:08 +0700
Subject: [PATCH 275/408] Add model 2023-11-16-bert_large_mrqa_en

---
 .../2023-11-16-bert_large_mrqa_en.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_large_mrqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_large_mrqa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_large_mrqa_en.md
new file mode 100644
index 00000000000000..eae0ea3a054696
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_large_mrqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_large_mrqa BertForQuestionAnswering from VMware
+author: John Snow Labs
+name: bert_large_mrqa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mrqa` is a English model originally trained by VMware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mrqa_en_5.2.0_3.0_1700161818217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mrqa_en_5.2.0_3.0_1700161818217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_mrqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_large_mrqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_mrqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/VMware/bert-large-mrqa
\ No newline at end of file

From 6653c104e0d0de6208d9f128114d3ef1f25931cb Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:27:46 +0700
Subject: [PATCH 276/408] Add model
 2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_en

---
 ...bert_qa_uncased_l_2_h_128_a_2_squad2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_en.md
new file mode 100644
index 00000000000000..4931b6a9da54eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_2_h_128_a_2_squad2
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-2_H-128_A-2_squad2` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_squad2_en_5.2.0_3.0_1700162863747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_squad2_en_5.2.0_3.0_1700162863747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_squad2","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_squad2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2.uncased_2l_128d_a2a_128d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_2_h_128_a_2_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-2_H-128_A-2_squad2
\ No newline at end of file

From 6d6da0dd5b693e20a0c61a7d0fd181dd2592b277 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:31:35 +0700
Subject: [PATCH 277/408] Add model
 2023-11-16-bert_base_uncased_finetuned_squad_aditya4521_en

---
 ...e_uncased_finetuned_squad_aditya4521_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad_aditya4521_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad_aditya4521_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad_aditya4521_en.md
new file mode 100644
index 00000000000000..cb89c8875cd53c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad_aditya4521_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_aditya4521 BertForQuestionAnswering from Aditya4521
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_aditya4521
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_aditya4521` is a English model originally trained by Aditya4521.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_aditya4521_en_5.2.0_3.0_1700163084328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_aditya4521_en_5.2.0_3.0_1700163084328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_aditya4521","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad_aditya4521", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_aditya4521|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Aditya4521/bert-base-uncased-finetuned-squad
\ No newline at end of file

From f9f76f4d8e1787455a2998fa1010561f1f2e7a79 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:32:35 +0700
Subject: [PATCH 278/408] Add model 2023-11-16-admisi_indobert_qna_v2_id

---
 .../2023-11-16-admisi_indobert_qna_v2_id.md   | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-admisi_indobert_qna_v2_id.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-admisi_indobert_qna_v2_id.md b/docs/_posts/ahmedlone127/2023-11-16-admisi_indobert_qna_v2_id.md
new file mode 100644
index 00000000000000..8b289b33b124c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-admisi_indobert_qna_v2_id.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Indonesian admisi_indobert_qna_v2 BertForQuestionAnswering from emny
+author: John Snow Labs
+name: admisi_indobert_qna_v2
+date: 2023-11-16
+tags: [bert, id, open_source, question_answering, onnx]
+task: Question Answering
+language: id
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`admisi_indobert_qna_v2` is a Indonesian model originally trained by emny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/admisi_indobert_qna_v2_id_5.2.0_3.0_1700163084339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/admisi_indobert_qna_v2_id_5.2.0_3.0_1700163084339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("admisi_indobert_qna_v2","id") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("admisi_indobert_qna_v2", "id")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|admisi_indobert_qna_v2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|id|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/emny/admisi-indobert-qna-v2
\ No newline at end of file

From b5cc5e1d92f4707a8068733a17bff087a22d4b09 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:41:06 +0700
Subject: [PATCH 279/408] Add model 2023-11-16-bert_squad_v2_en

---
 .../2023-11-16-bert_squad_v2_en.md            | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_squad_v2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_squad_v2_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_squad_v2_en.md
new file mode 100644
index 00000000000000..4f7e0cf4b8681f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_squad_v2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_squad_v2 BertForQuestionAnswering from fahmiaziz
+author: John Snow Labs
+name: bert_squad_v2
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_v2` is a English model originally trained by fahmiaziz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_v2_en_5.2.0_3.0_1700163659003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_v2_en_5.2.0_3.0_1700163659003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_squad_v2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_squad_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_v2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/fahmiaziz/bert-squad-v2
\ No newline at end of file

From 700d478e903413c31314cc228131b9ac5f1d7e3a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 02:42:07 +0700
Subject: [PATCH 280/408] Add model
 2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en

---
 ...cased_l_2_h_128_a_2_squad2_covid_qna_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en.md
new file mode 100644
index 00000000000000..e26b351b192a8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from aodiniz)
+author: John Snow Labs
+name: bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_uncased_L-2_H-128_A-2_squad2_covid-qna` is a English model originally trained by `aodiniz`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en_5.2.0_3.0_1700163669992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna_en_5.2.0_3.0_1700163669992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+ 
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.squadv2_covid.uncased_2l_128d_a2a_128d").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_uncased_l_2_h_128_a_2_squad2_covid_qna|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/aodiniz/bert_uncased_L-2_H-128_A-2_squad2_covid-qna
\ No newline at end of file

From a2788d16d5498fc7fd322e35ca6476d431469941 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 03:04:28 +0700
Subject: [PATCH 281/408] Add model 2023-11-16-xtremeqa_arabic_ar

---
 .../2023-11-16-xtremeqa_arabic_ar.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-xtremeqa_arabic_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-xtremeqa_arabic_ar.md b/docs/_posts/ahmedlone127/2023-11-16-xtremeqa_arabic_ar.md
new file mode 100644
index 00000000000000..71dc9912ba9e40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-xtremeqa_arabic_ar.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Arabic xtremeqa_arabic BertForQuestionAnswering from abdalrahmanshahrour
+author: John Snow Labs
+name: xtremeqa_arabic
+date: 2023-11-16
+tags: [bert, ar, open_source, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xtremeqa_arabic` is a Arabic model originally trained by abdalrahmanshahrour.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xtremeqa_arabic_ar_5.2.0_3.0_1700165065844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xtremeqa_arabic_ar_5.2.0_3.0_1700165065844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("xtremeqa_arabic","ar") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("xtremeqa_arabic", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xtremeqa_arabic|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|84.2 MB|
+
+## References
+
+https://huggingface.co/abdalrahmanshahrour/xtremeQA-ar
\ No newline at end of file

From ff10aa4fb5031af92719d66bac8f2b404f9bfd25 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 03:05:36 +0700
Subject: [PATCH 282/408] Add model 2023-11-16-shivamqa_en

---
 .../ahmedlone127/2023-11-16-shivamqa_en.md    | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-shivamqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-shivamqa_en.md b/docs/_posts/ahmedlone127/2023-11-16-shivamqa_en.md
new file mode 100644
index 00000000000000..2cc4897429d4fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-shivamqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English shivamqa BertForQuestionAnswering from Shivam22182
+author: John Snow Labs
+name: shivamqa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shivamqa` is a English model originally trained by Shivam22182.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shivamqa_en_5.2.0_3.0_1700165128883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shivamqa_en_5.2.0_3.0_1700165128883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("shivamqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("shivamqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|shivamqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Shivam22182/ShivamQA
\ No newline at end of file

From 68821d99bf0a4603af2e4d12161ad8b0ad2d0c84 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:10:55 +0700
Subject: [PATCH 283/408] Add model 2023-11-16-rinna_arabert_qa_ar2_en

---
 .../2023-11-16-rinna_arabert_qa_ar2_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-rinna_arabert_qa_ar2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-rinna_arabert_qa_ar2_en.md b/docs/_posts/ahmedlone127/2023-11-16-rinna_arabert_qa_ar2_en.md
new file mode 100644
index 00000000000000..8b3589adaf57d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-rinna_arabert_qa_ar2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English rinna_arabert_qa_ar2 BertForQuestionAnswering from Echiguerkh
+author: John Snow Labs
+name: rinna_arabert_qa_ar2
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rinna_arabert_qa_ar2` is a English model originally trained by Echiguerkh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rinna_arabert_qa_ar2_en_5.2.0_3.0_1700169044586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rinna_arabert_qa_ar2_en_5.2.0_3.0_1700169044586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("rinna_arabert_qa_ar2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("rinna_arabert_qa_ar2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rinna_arabert_qa_ar2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|504.9 MB|
+
+## References
+
+https://huggingface.co/Echiguerkh/rinna-arabert-qa-ar2
\ No newline at end of file

From 4c00992a4101e5504b8081e010f898c9c11c922c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:11:55 +0700
Subject: [PATCH 284/408] Add model
 2023-11-16-ixambert_finetuned_squad_basque_english_en

---
 ...mbert_finetuned_squad_basque_english_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-ixambert_finetuned_squad_basque_english_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-ixambert_finetuned_squad_basque_english_en.md b/docs/_posts/ahmedlone127/2023-11-16-ixambert_finetuned_squad_basque_english_en.md
new file mode 100644
index 00000000000000..8d49d33b5f49a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-ixambert_finetuned_squad_basque_english_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English ixambert_finetuned_squad_basque_english BertForQuestionAnswering from MarcBrun
+author: John Snow Labs
+name: ixambert_finetuned_squad_basque_english
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ixambert_finetuned_squad_basque_english` is a English model originally trained by MarcBrun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ixambert_finetuned_squad_basque_english_en_5.2.0_3.0_1700169065920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ixambert_finetuned_squad_basque_english_en_5.2.0_3.0_1700169065920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ixambert_finetuned_squad_basque_english","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ixambert_finetuned_squad_basque_english", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ixambert_finetuned_squad_basque_english|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|661.1 MB|
+
+## References
+
+https://huggingface.co/MarcBrun/ixambert-finetuned-squad-eu-en
\ No newline at end of file

From 4d866e3eed334305c5437a0ebd6c4a386c2a5c5f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:28:45 +0700
Subject: [PATCH 285/408] Add model
 2023-11-16-electra_qa_biomedtra_small_spanish_squad2_es

---
 ...ra_qa_biomedtra_small_spanish_squad2_es.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_biomedtra_small_spanish_squad2_es.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biomedtra_small_spanish_squad2_es.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biomedtra_small_spanish_squad2_es.md
new file mode 100644
index 00000000000000..2addac899e4323
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_biomedtra_small_spanish_squad2_es.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Castilian, Spanish electra_qa_biomedtra_small_spanish_squad2 BertForQuestionAnswering from hackathon-pln-es
+author: John Snow Labs
+name: electra_qa_biomedtra_small_spanish_squad2
+date: 2023-11-16
+tags: [bert, es, open_source, question_answering, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_qa_biomedtra_small_spanish_squad2` is a Castilian, Spanish model originally trained by hackathon-pln-es.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_biomedtra_small_spanish_squad2_es_5.2.0_3.0_1700170121774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_biomedtra_small_spanish_squad2_es_5.2.0_3.0_1700170121774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_biomedtra_small_spanish_squad2","es") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("electra_qa_biomedtra_small_spanish_squad2", "es")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_biomedtra_small_spanish_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|51.2 MB|
+
+## References
+
+https://huggingface.co/hackathon-pln-es/biomedtra-small-es-squad2-es
\ No newline at end of file

From a367805521087fe4f623957b6350c22399027835 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:34:32 +0700
Subject: [PATCH 286/408] Add model
 2023-11-16-ntu_adl_span_selection_macbert_en

---
 ...11-16-ntu_adl_span_selection_macbert_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_macbert_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_macbert_en.md b/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_macbert_en.md
new file mode 100644
index 00000000000000..2e9f16ddd93117
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-ntu_adl_span_selection_macbert_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English ntu_adl_span_selection_macbert BertForQuestionAnswering from xjlulu
+author: John Snow Labs
+name: ntu_adl_span_selection_macbert
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ntu_adl_span_selection_macbert` is a English model originally trained by xjlulu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_macbert_en_5.2.0_3.0_1700170463920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_macbert_en_5.2.0_3.0_1700170463920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ntu_adl_span_selection_macbert","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ntu_adl_span_selection_macbert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ntu_adl_span_selection_macbert|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.1 MB|
+
+## References
+
+https://huggingface.co/xjlulu/ntu_adl_span_selection_macbert
\ No newline at end of file

From c7efd37d97143452b587cef315e998cba9ec678d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:35:32 +0700
Subject: [PATCH 287/408] Add model
 2023-11-16-bert_finetuned_squad_accelerate_quangb1910128_en

---
 ...tuned_squad_accelerate_quangb1910128_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_accelerate_quangb1910128_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_accelerate_quangb1910128_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_accelerate_quangb1910128_en.md
new file mode 100644
index 00000000000000..9e215166d37f59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_accelerate_quangb1910128_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_accelerate_quangb1910128 BertForQuestionAnswering from quangb1910128
+author: John Snow Labs
+name: bert_finetuned_squad_accelerate_quangb1910128
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_quangb1910128` is a English model originally trained by quangb1910128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_quangb1910128_en_5.2.0_3.0_1700170476755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_quangb1910128_en_5.2.0_3.0_1700170476755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_quangb1910128","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_accelerate_quangb1910128", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_accelerate_quangb1910128|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/quangb1910128/bert-finetuned-squad-accelerate
\ No newline at end of file

From 5f3750873a3dc02c777a6ec09807a913878a9599 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:47:33 +0700
Subject: [PATCH 288/408] Add model
 2023-11-16-bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en

---
 ..._spanish_wwm_cased_finetuned_qa_mlqa_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en.md
new file mode 100644
index 00000000000000..08d38904f60b2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_spanish_wwm_cased_finetuned_qa_mlqa BertForQuestionAnswering from dccuchile
+author: John Snow Labs
+name: bert_base_spanish_wwm_cased_finetuned_qa_mlqa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_qa_mlqa` is a English model originally trained by dccuchile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en_5.2.0_3.0_1700171245676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_qa_mlqa_en_5.2.0_3.0_1700171245676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_spanish_wwm_cased_finetuned_qa_mlqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_spanish_wwm_cased_finetuned_qa_mlqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_spanish_wwm_cased_finetuned_qa_mlqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa
\ No newline at end of file

From bcf60396015e35ea8827cfda471f691ac80192b2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:48:33 +0700
Subject: [PATCH 289/408] Add model
 2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en

---
 ...ed_tquad_finetuned_lr_2e_05_epochs_9_en.md | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en.md
new file mode 100644
index 00000000000000..95deab0edacba9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en.md
@@ -0,0 +1,95 @@
+---
+layout: model
+title: English bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9 BertForQuestionAnswering from husnu
+author: John Snow Labs
+name: bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9` is a English model originally trained by husnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en_5.2.0_3.0_1700171301368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9_en_5.2.0_3.0_1700171301368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l6_h256_uncased_tquad_finetuned_lr_2e_05_epochs_9|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|47.3 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+https://huggingface.co/husnu/xtremedistil-l6-h256-uncased-TQUAD-finetuned_lr-2e-05_epochs-9
\ No newline at end of file

From 4bdd9cd0a726a1211e1eba0dbcc8690f405b3515 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:53:00 +0700
Subject: [PATCH 290/408] Add model 2023-11-16-electra_qa_elctrafp_en

---
 .../2023-11-16-electra_qa_elctrafp_en.md      | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_elctrafp_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_elctrafp_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_elctrafp_en.md
new file mode 100644
index 00000000000000..6766d581315d0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_elctrafp_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from carlosserquen)
+author: John Snow Labs
+name: electra_qa_elctrafp
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electrafp` is a English model originally trained by `carlosserquen`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_elctrafp_en_5.2.0_3.0_1700171578206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_elctrafp_en_5.2.0_3.0_1700171578206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_elctrafp","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_elctrafp","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.electra.by_carlosserquen").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_elctrafp|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/carlosserquen/electrafp
\ No newline at end of file

From 32423ec78cd2b951599a3be714315074e0d0c7df Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 04:58:16 +0700
Subject: [PATCH 291/408] Add model
 2023-11-16-chinese_bert_wwm_ext_finetuned_qa_b8_10_en

---
 ...nese_bert_wwm_ext_finetuned_qa_b8_10_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-chinese_bert_wwm_ext_finetuned_qa_b8_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-chinese_bert_wwm_ext_finetuned_qa_b8_10_en.md b/docs/_posts/ahmedlone127/2023-11-16-chinese_bert_wwm_ext_finetuned_qa_b8_10_en.md
new file mode 100644
index 00000000000000..4889a74dde463f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-chinese_bert_wwm_ext_finetuned_qa_b8_10_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English chinese_bert_wwm_ext_finetuned_qa_b8_10 BertForQuestionAnswering from sharkMeow
+author: John Snow Labs
+name: chinese_bert_wwm_ext_finetuned_qa_b8_10
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_bert_wwm_ext_finetuned_qa_b8_10` is a English model originally trained by sharkMeow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_bert_wwm_ext_finetuned_qa_b8_10_en_5.2.0_3.0_1700171888784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_bert_wwm_ext_finetuned_qa_b8_10_en_5.2.0_3.0_1700171888784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("chinese_bert_wwm_ext_finetuned_qa_b8_10","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("chinese_bert_wwm_ext_finetuned_qa_b8_10", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_bert_wwm_ext_finetuned_qa_b8_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.2 MB|
+
+## References
+
+https://huggingface.co/sharkMeow/chinese-bert-wwm-ext-finetuned-QA-b8-10
\ No newline at end of file

From d3b3422c17b82bd342ee2fc1720460d5ca516b0f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 05:00:10 +0700
Subject: [PATCH 292/408] Add model 2023-11-16-biomedical_question_answering_en

---
 ...-11-16-biomedical_question_answering_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-biomedical_question_answering_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-biomedical_question_answering_en.md b/docs/_posts/ahmedlone127/2023-11-16-biomedical_question_answering_en.md
new file mode 100644
index 00000000000000..69ac65b6d01e8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-biomedical_question_answering_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English biomedical_question_answering BertForQuestionAnswering from Shushant
+author: John Snow Labs
+name: biomedical_question_answering
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomedical_question_answering` is a English model originally trained by Shushant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomedical_question_answering_en_5.2.0_3.0_1700172001885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomedical_question_answering_en_5.2.0_3.0_1700172001885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("biomedical_question_answering","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("biomedical_question_answering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomedical_question_answering|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/Shushant/biomedical_question_answering
\ No newline at end of file

From 994c39593752cb2793d0866942ea202c60cdf080 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 05:08:06 +0700
Subject: [PATCH 293/408] Add model 2023-11-16-stackoverflow_qa_en

---
 .../2023-11-16-stackoverflow_qa_en.md         | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-stackoverflow_qa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-stackoverflow_qa_en.md b/docs/_posts/ahmedlone127/2023-11-16-stackoverflow_qa_en.md
new file mode 100644
index 00000000000000..612034c338beea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-stackoverflow_qa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English stackoverflow_qa BertForQuestionAnswering from pacovaldez
+author: John Snow Labs
+name: stackoverflow_qa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stackoverflow_qa` is a English model originally trained by pacovaldez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stackoverflow_qa_en_5.2.0_3.0_1700172479295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stackoverflow_qa_en_5.2.0_3.0_1700172479295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("stackoverflow_qa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("stackoverflow_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stackoverflow_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/pacovaldez/stackoverflow-qa
\ No newline at end of file

From 2f90a46d5176d641e3a8965f71cbd56423a3e36e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 05:10:25 +0700
Subject: [PATCH 294/408] Add model
 2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en

---
 ...h256_uncased_natural_questions_short_en.md | 102 ++++++++++++++++++
 1 file changed, 102 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en.md
new file mode 100644
index 00000000000000..61b969172571d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en.md
@@ -0,0 +1,102 @@
+---
+layout: model
+title: English BertForQuestionAnswering Uncased model (from Be-Lo)
+author: John Snow Labs
+name: bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short
+date: 2023-11-16
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xtremedistil-l6-h256-uncased-natural-questions-short` is a English model originally trained by `Be-Lo`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en_5.2.0_3.0_1700172621685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short_en_5.2.0_3.0_1700172621685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_xtremedistil_l6_h256_uncased_natural_questions_short|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|47.4 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Be-Lo/xtremedistil-l6-h256-uncased-natural-questions-short
+- https://research.google/pubs/pub47761/
+- https://github.com/mrqa/MRQA-Shared-Task-2019
+- https://research.google/pubs/pub47761/
+- https://github.com/mrqa/MRQA-Shared-Task-2019
+- https://square.ukp-lab.de/qa
+- https://www.informatik.tu-darmstadt.de/ukp/ukp_home/index.en.jsp
+- https://github.com/dl4nlp-tuda/deep-learning-for-nlp-lectures
+- https://www.trusthlt.org/
\ No newline at end of file

From 074b2a287ffc61d6f7a525946e79d718c4a5bb2c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 05:30:47 +0700
Subject: [PATCH 295/408] Add model
 2023-11-16-bert_finetuned_squad_v1_francesco_a_en

---
 ...-bert_finetuned_squad_v1_francesco_a_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_v1_francesco_a_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_v1_francesco_a_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_v1_francesco_a_en.md
new file mode 100644
index 00000000000000..7de4975b8b6635
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_v1_francesco_a_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_v1_francesco_a BertForQuestionAnswering from Francesco-A
+author: John Snow Labs
+name: bert_finetuned_squad_v1_francesco_a
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_v1_francesco_a` is a English model originally trained by Francesco-A.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_v1_francesco_a_en_5.2.0_3.0_1700173829042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_v1_francesco_a_en_5.2.0_3.0_1700173829042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_v1_francesco_a","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_v1_francesco_a", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_v1_francesco_a|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Francesco-A/bert-finetuned-squad-v1
\ No newline at end of file

From 403d203bf176c0b3966e1b85b5139bf0f7652d27 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 05:55:53 +0700
Subject: [PATCH 296/408] Add model
 2023-11-16-electra_qa_small_discriminator_finetuned_squad_2_en

---
 ...mall_discriminator_finetuned_squad_2_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_discriminator_finetuned_squad_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_discriminator_finetuned_squad_2_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_discriminator_finetuned_squad_2_en.md
new file mode 100644
index 00000000000000..7d044fab1fbe4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_discriminator_finetuned_squad_2_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from bdickson) Version-2
+author: John Snow Labs
+name: electra_qa_small_discriminator_finetuned_squad_2
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-small-discriminator-finetuned-squad-finetuned-squad` is a English model originally trained by `bdickson`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_small_discriminator_finetuned_squad_2_en_5.2.0_3.0_1700175351592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_small_discriminator_finetuned_squad_2_en_5.2.0_3.0_1700175351592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_small_discriminator_finetuned_squad_2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_small_discriminator_finetuned_squad_2","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.small_v2.by_bdickson").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_small_discriminator_finetuned_squad_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/bdickson/electra-small-discriminator-finetuned-squad-finetuned-squad
\ No newline at end of file

From 6f783bed77c93c178b06c8a62113ab7cc27fdd46 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 05:56:55 +0700
Subject: [PATCH 297/408] Add model 2023-11-16-mbert_squad2_webis_id

---
 .../2023-11-16-mbert_squad2_webis_id.md       | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-mbert_squad2_webis_id.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-mbert_squad2_webis_id.md b/docs/_posts/ahmedlone127/2023-11-16-mbert_squad2_webis_id.md
new file mode 100644
index 00000000000000..a96752fb36ae8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-mbert_squad2_webis_id.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Indonesian mbert_squad2_webis BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: mbert_squad2_webis
+date: 2023-11-16
+tags: [bert, id, open_source, question_answering, onnx]
+task: Question Answering
+language: id
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_squad2_webis` is a Indonesian model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_squad2_webis_id_5.2.0_3.0_1700175351684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_squad2_webis_id_5.2.0_3.0_1700175351684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mbert_squad2_webis","id") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("mbert_squad2_webis", "id")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_squad2_webis|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|id|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/intanm/mbert-squad2-webis
\ No newline at end of file

From f2166f97eb7a346d109fec9dd37df0dd0268ee22 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:01:29 +0700
Subject: [PATCH 298/408] Add model
 2023-11-16-electra_qa_base_discriminator_finetuned_squadv2_tr

---
 ...base_discriminator_finetuned_squadv2_tr.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv2_tr.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv2_tr.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv2_tr.md
new file mode 100644
index 00000000000000..214d1d5b7b8fac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_discriminator_finetuned_squadv2_tr.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Turkish ElectraForQuestionAnswering model (from enelpi) Discriminator Version-2
+author: John Snow Labs
+name: electra_qa_base_discriminator_finetuned_squadv2
+date: 2023-11-16
+tags: [tr, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-discriminator-finetuned_squadv2_tr` is a Turkish model originally trained by `enelpi`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_discriminator_finetuned_squadv2_tr_5.2.0_3.0_1700175680958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_discriminator_finetuned_squadv2_tr_5.2.0_3.0_1700175680958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_discriminator_finetuned_squadv2","tr") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_discriminator_finetuned_squadv2","tr") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("Benim adım ne?", "Benim adım Clara ve Berkeley'de yaşıyorum.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("tr.answer_question.squadv2.electra.base_v2").predict("""Benim adım ne?|||"Benim adım Clara ve Berkeley'de yaşıyorum.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_discriminator_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|412.2 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/enelpi/electra-base-discriminator-finetuned_squadv2_tr
\ No newline at end of file

From 770e63aa87874673626d5f1833d5947e5a2a5b16 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:05:08 +0700
Subject: [PATCH 299/408] Add model 2023-11-16-bert_finetuned_squad_alaa1234_en

---
 ...-11-16-bert_finetuned_squad_alaa1234_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_alaa1234_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_alaa1234_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_alaa1234_en.md
new file mode 100644
index 00000000000000..4af38d566273b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_alaa1234_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_alaa1234 BertForQuestionAnswering from alaa1234
+author: John Snow Labs
+name: bert_finetuned_squad_alaa1234
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_alaa1234` is a English model originally trained by alaa1234.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alaa1234_en_5.2.0_3.0_1700175900118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alaa1234_en_5.2.0_3.0_1700175900118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_alaa1234","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_alaa1234", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_alaa1234|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/alaa1234/bert-finetuned-squad
\ No newline at end of file

From 630f944bbcf41674c1a1735bd37bd075a8682bec Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:06:08 +0700
Subject: [PATCH 300/408] Add model 2023-11-16-extractive_reader_nq_en

---
 .../2023-11-16-extractive_reader_nq_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-extractive_reader_nq_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-extractive_reader_nq_en.md b/docs/_posts/ahmedlone127/2023-11-16-extractive_reader_nq_en.md
new file mode 100644
index 00000000000000..f923acc622fb2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-extractive_reader_nq_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English extractive_reader_nq BertForQuestionAnswering from ToluClassics
+author: John Snow Labs
+name: extractive_reader_nq
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`extractive_reader_nq` is a English model originally trained by ToluClassics.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/extractive_reader_nq_en_5.2.0_3.0_1700175915496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/extractive_reader_nq_en_5.2.0_3.0_1700175915496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("extractive_reader_nq","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("extractive_reader_nq", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|extractive_reader_nq|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/ToluClassics/extractive_reader_nq
\ No newline at end of file

From 1df58bf1e95ea961b1d23706d821c791d537ac04 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:20:05 +0700
Subject: [PATCH 301/408] Add model
 2023-11-16-electra_qa_small_finetuned_squadv2_en

---
 ...6-electra_qa_small_finetuned_squadv2_en.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..404f385ec0eb37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_small_finetuned_squadv2_en.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering Small model (from mrm8488) Version-2
+author: John Snow Labs
+name: electra_qa_small_finetuned_squadv2
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-small-finetuned-squadv2` is a English model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_small_finetuned_squadv2_en_5.2.0_3.0_1700176800464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_small_finetuned_squadv2_en_5.2.0_3.0_1700176800464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_small_finetuned_squadv2","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_small_finetuned_squadv2","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.electra.small_v2").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_small_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/electra-small-finetuned-squadv2
+- https://rajpurkar.github.io/SQuAD-explorer/explore/v2.0/dev/
\ No newline at end of file

From d2c9e3ec1d483003b0b4f6340b448da2f63c47a7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:21:09 +0700
Subject: [PATCH 302/408] Add model 2023-11-16-bert_finetuned_squad_shafa_en

---
 ...023-11-16-bert_finetuned_squad_shafa_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shafa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shafa_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shafa_en.md
new file mode 100644
index 00000000000000..21201b1e57a0ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_shafa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_shafa BertForQuestionAnswering from shafa
+author: John Snow Labs
+name: bert_finetuned_squad_shafa
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_shafa` is a English model originally trained by shafa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_shafa_en_5.2.0_3.0_1700176862417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_shafa_en_5.2.0_3.0_1700176862417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_shafa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_shafa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_shafa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/shafa/bert-finetuned-squad
\ No newline at end of file

From badd78ad038455a17f9cc735ae5d5765ecb52eb5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:25:43 +0700
Subject: [PATCH 303/408] Add model 2023-11-16-ia_llama_en

---
 .../ahmedlone127/2023-11-16-ia_llama_en.md    | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-ia_llama_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-ia_llama_en.md b/docs/_posts/ahmedlone127/2023-11-16-ia_llama_en.md
new file mode 100644
index 00000000000000..9ac7ace29b37bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-ia_llama_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English ia_llama BertForQuestionAnswering from nordGARA
+author: John Snow Labs
+name: ia_llama
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ia_llama` is a English model originally trained by nordGARA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ia_llama_en_5.2.0_3.0_1700177131200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ia_llama_en_5.2.0_3.0_1700177131200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ia_llama","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ia_llama", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ia_llama|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/nordGARA/IA-LLAMA
\ No newline at end of file

From aa13cdcf0372811f5c30f00b6bfc49e72fed3156 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:33:33 +0700
Subject: [PATCH 304/408] Add model
 2023-11-16-question_answering_arabert_xtreme_arabic_ar

---
 ...tion_answering_arabert_xtreme_arabic_ar.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-question_answering_arabert_xtreme_arabic_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-question_answering_arabert_xtreme_arabic_ar.md b/docs/_posts/ahmedlone127/2023-11-16-question_answering_arabert_xtreme_arabic_ar.md
new file mode 100644
index 00000000000000..aa9ad3eec4e617
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-question_answering_arabert_xtreme_arabic_ar.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Arabic question_answering_arabert_xtreme_arabic BertForQuestionAnswering from MMars
+author: John Snow Labs
+name: question_answering_arabert_xtreme_arabic
+date: 2023-11-16
+tags: [bert, ar, open_source, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_arabert_xtreme_arabic` is a Arabic model originally trained by MMars.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_arabert_xtreme_arabic_ar_5.2.0_3.0_1700177599845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_arabert_xtreme_arabic_ar_5.2.0_3.0_1700177599845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("question_answering_arabert_xtreme_arabic","ar") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("question_answering_arabert_xtreme_arabic", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_arabert_xtreme_arabic|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|504.8 MB|
+
+## References
+
+https://huggingface.co/MMars/Question_Answering_AraBERT_xtreme_ar
\ No newline at end of file

From f8fb4492ed00aa2ba3dcf835aba6123649ad044b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:34:33 +0700
Subject: [PATCH 305/408] Add model
 2023-11-16-electra_qa_base_squad2_covid_deepset_en

---
 ...electra_qa_base_squad2_covid_deepset_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_covid_deepset_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_covid_deepset_en.md b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_covid_deepset_en.md
new file mode 100644
index 00000000000000..ae2ce811601541
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-electra_qa_base_squad2_covid_deepset_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from armageddon)
+author: John Snow Labs
+name: electra_qa_base_squad2_covid_deepset
+date: 2023-11-16
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-squad2-covid-qa-deepset` is a English model originally trained by `armageddon`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_base_squad2_covid_deepset_en_5.2.0_3.0_1700177599963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_squad2_covid_deepset_en_5.2.0_3.0_1700177599963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_squad2_covid_deepset","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_squad2_covid_deepset","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2_covid.electra.base").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_squad2_covid_deepset|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/armageddon/electra-base-squad2-covid-qa-deepset
\ No newline at end of file

From 97ee87526af6d3ec30fe2302ce7bf472b784a2ee Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:51:45 +0700
Subject: [PATCH 306/408] Add model
 2023-11-16-bert_base_uncased_finetuned_squad2_iproject_10_en

---
 ...uncased_finetuned_squad2_iproject_10_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad2_iproject_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad2_iproject_10_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad2_iproject_10_en.md
new file mode 100644
index 00000000000000..03c4eebedd62af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_base_uncased_finetuned_squad2_iproject_10_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad2_iproject_10 BertForQuestionAnswering from IProject-10
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad2_iproject_10
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad2_iproject_10` is a English model originally trained by IProject-10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad2_iproject_10_en_5.2.0_3.0_1700178697409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad2_iproject_10_en_5.2.0_3.0_1700178697409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad2_iproject_10","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad2_iproject_10", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad2_iproject_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IProject-10/bert-base-uncased-finetuned-squad2
\ No newline at end of file

From b0966c2ba7014dd1d7f6421f1ebf27c07fbdc86e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:57:15 +0700
Subject: [PATCH 307/408] Add model 2023-11-16-bert_covid_10_en

---
 .../2023-11-16-bert_covid_10_en.md            | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_covid_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_covid_10_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_covid_10_en.md
new file mode 100644
index 00000000000000..c0a77af1e025e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_covid_10_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_covid_10 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_covid_10
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_covid_10` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_covid_10_en_5.2.0_3.0_1700179027577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_covid_10_en_5.2.0_3.0_1700179027577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_covid_10","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_covid_10", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_covid_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-covid-10
\ No newline at end of file

From eb49c0c74e5eceef062d60cc521691de5992488a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 06:59:39 +0700
Subject: [PATCH 308/408] Add model
 2023-11-16-bert_finetuned_squad_technicalmorujiii_en

---
 ...rt_finetuned_squad_technicalmorujiii_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_technicalmorujiii_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_technicalmorujiii_en.md b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_technicalmorujiii_en.md
new file mode 100644
index 00000000000000..b628a0e32536cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-16-bert_finetuned_squad_technicalmorujiii_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_technicalmorujiii BertForQuestionAnswering from TechnicalMoruJiii
+author: John Snow Labs
+name: bert_finetuned_squad_technicalmorujiii
+date: 2023-11-16
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_technicalmorujiii` is a English model originally trained by TechnicalMoruJiii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_technicalmorujiii_en_5.2.0_3.0_1700179171257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_technicalmorujiii_en_5.2.0_3.0_1700179171257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_technicalmorujiii","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_technicalmorujiii", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_technicalmorujiii|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/TechnicalMoruJiii/bert-finetuned-squad
\ No newline at end of file

From 7f7c99b996303988dc9bbb8b499cfbd2b7a739e3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:21:07 +0700
Subject: [PATCH 309/408] Add model 2023-11-17-bert_31_en

---
 .../ahmedlone127/2023-11-17-bert_31_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_31_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_31_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_31_en.md
new file mode 100644
index 00000000000000..a6df8bc322ceb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_31_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_31 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_31
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_31` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_31_en_5.2.0_3.0_1700180456553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_31_en_5.2.0_3.0_1700180456553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_31","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_31", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_31|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-31
\ No newline at end of file

From 4c96cfd601f79fc7583d2d551bb5fd60d9f66290 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:23:08 +0700
Subject: [PATCH 310/408] Add model
 2023-11-17-bert_base_cased_healthdemomodel_en

---
 ...1-17-bert_base_cased_healthdemomodel_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_cased_healthdemomodel_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_cased_healthdemomodel_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_cased_healthdemomodel_en.md
new file mode 100644
index 00000000000000..a62ba3ee4d3112
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_cased_healthdemomodel_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_cased_healthdemomodel BertForQuestionAnswering from pythonist
+author: John Snow Labs
+name: bert_base_cased_healthdemomodel
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_healthdemomodel` is a English model originally trained by pythonist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_healthdemomodel_en_5.2.0_3.0_1700180576373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_healthdemomodel_en_5.2.0_3.0_1700180576373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_healthdemomodel","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_cased_healthdemomodel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_healthdemomodel|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/pythonist/bert-base-cased-healthdemomodel
\ No newline at end of file

From 00849c0610f0ebc157038a35e9ddcd1debea329f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:24:08 +0700
Subject: [PATCH 311/408] Add model
 2023-11-17-bert_base_uncased_finetuned_squad_v2_seviladiguzel_en

---
 ...sed_finetuned_squad_v2_seviladiguzel_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_seviladiguzel_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_seviladiguzel_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_seviladiguzel_en.md
new file mode 100644
index 00000000000000..218e2daa73aace
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_seviladiguzel_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_v2_seviladiguzel BertForQuestionAnswering from seviladiguzel
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_v2_seviladiguzel
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_v2_seviladiguzel` is a English model originally trained by seviladiguzel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_v2_seviladiguzel_en_5.2.0_3.0_1700180576351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_v2_seviladiguzel_en_5.2.0_3.0_1700180576351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_v2_seviladiguzel","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad_v2_seviladiguzel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_v2_seviladiguzel|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/seviladiguzel/bert-base-uncased-finetuned-squad_v2
\ No newline at end of file

From 0ae1ffb396167aea7099b5d93f45ba5538d82c19 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:25:09 +0700
Subject: [PATCH 312/408] Add model
 2023-11-17-electra_qa_electricidad_small_finetuned_squadv1_es

---
 ...electricidad_small_finetuned_squadv1_es.md | 101 ++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-electra_qa_electricidad_small_finetuned_squadv1_es.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-electra_qa_electricidad_small_finetuned_squadv1_es.md b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_electricidad_small_finetuned_squadv1_es.md
new file mode 100644
index 00000000000000..67f289bded9149
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_electricidad_small_finetuned_squadv1_es.md
@@ -0,0 +1,101 @@
+---
+layout: model
+title: Spanish ElectraForQuestionAnswering Small model (from mrm8488)
+author: John Snow Labs
+name: electra_qa_electricidad_small_finetuned_squadv1
+date: 2023-11-17
+tags: [es, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: es
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electricidad-small-finetuned-squadv1-es` is a Spanish model originally trained by `mrm8488`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_electricidad_small_finetuned_squadv1_es_5.2.0_3.0_1700180656189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_electricidad_small_finetuned_squadv1_es_5.2.0_3.0_1700180656189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_electricidad_small_finetuned_squadv1","es") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["¿Cuál es mi nombre?", "Mi nombre es Clara y vivo en Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_electricidad_small_finetuned_squadv1","es") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("¿Cuál es mi nombre?", "Mi nombre es Clara y vivo en Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("es.answer_question.squad.electra.small").predict("""¿Cuál es mi nombre?|||"Mi nombre es Clara y vivo en Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_electricidad_small_finetuned_squadv1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|es|
+|Size:|50.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/mrm8488/electricidad-small-finetuned-squadv1-es
+- https://github.com/ccasimiro88/TranslateAlignRetrieve/tree/master/SQuAD-es-v1.1
\ No newline at end of file

From 24377fcadb479c7e4b1af9ed6bf8bcea070478d8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:26:09 +0700
Subject: [PATCH 313/408] Add model
 2023-11-17-bert_large_question_answering_finetuned_legal_en

---
 ...e_question_answering_finetuned_legal_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_large_question_answering_finetuned_legal_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_large_question_answering_finetuned_legal_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_large_question_answering_finetuned_legal_en.md
new file mode 100644
index 00000000000000..402d4dd6d33147
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_large_question_answering_finetuned_legal_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_large_question_answering_finetuned_legal BertForQuestionAnswering from atharvamundada99
+author: John Snow Labs
+name: bert_large_question_answering_finetuned_legal
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_question_answering_finetuned_legal` is a English model originally trained by atharvamundada99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_question_answering_finetuned_legal_en_5.2.0_3.0_1700180647015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_question_answering_finetuned_legal_en_5.2.0_3.0_1700180647015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_question_answering_finetuned_legal","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_large_question_answering_finetuned_legal", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_question_answering_finetuned_legal|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/atharvamundada99/bert-large-question-answering-finetuned-legal
\ No newline at end of file

From de2fa411db8945478b935920074dec87183f255f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:50:33 +0700
Subject: [PATCH 314/408] Add model 2023-11-17-bert_finetuned_squad_sneh1th_en

---
 ...3-11-17-bert_finetuned_squad_sneh1th_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sneh1th_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sneh1th_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sneh1th_en.md
new file mode 100644
index 00000000000000..f754283824a42d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sneh1th_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_sneh1th BertForQuestionAnswering from sneh1th
+author: John Snow Labs
+name: bert_finetuned_squad_sneh1th
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_sneh1th` is a English model originally trained by sneh1th.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sneh1th_en_5.2.0_3.0_1700182220425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sneh1th_en_5.2.0_3.0_1700182220425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_sneh1th","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_sneh1th", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_sneh1th|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/sneh1th/bert-finetuned-squad
\ No newline at end of file

From 450acfaa6ce400503dd7444e52b8bc7837769257 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:51:33 +0700
Subject: [PATCH 315/408] Add model
 2023-11-17-bert_base_uncased_finetuned_squad_finetuned_nq_en

---
 ...uncased_finetuned_squad_finetuned_nq_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_finetuned_nq_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_finetuned_nq_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_finetuned_nq_en.md
new file mode 100644
index 00000000000000..89ae9c50efcafc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_finetuned_nq_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_finetuned_nq BertForQuestionAnswering from leonardoschluter
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_finetuned_nq
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_finetuned_nq` is a English model originally trained by leonardoschluter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_finetuned_nq_en_5.2.0_3.0_1700182220379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_finetuned_nq_en_5.2.0_3.0_1700182220379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_finetuned_nq","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad_finetuned_nq", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_finetuned_nq|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/leonardoschluter/bert-base-uncased-finetuned-squad-finetuned-nq
\ No newline at end of file

From e74f19458fc63566599efa83c0e9bfe177467249 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:52:57 +0700
Subject: [PATCH 316/408] Add model
 2023-11-17-bert_base_finnish_cased_squad2_fi

---
 ...11-17-bert_base_finnish_cased_squad2_fi.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_finnish_cased_squad2_fi.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_finnish_cased_squad2_fi.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_finnish_cased_squad2_fi.md
new file mode 100644
index 00000000000000..e283cc51047771
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_finnish_cased_squad2_fi.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Finnish bert_base_finnish_cased_squad2 BertForQuestionAnswering from TurkuNLP
+author: John Snow Labs
+name: bert_base_finnish_cased_squad2
+date: 2023-11-17
+tags: [bert, fi, open_source, question_answering, onnx]
+task: Question Answering
+language: fi
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finnish_cased_squad2` is a Finnish model originally trained by TurkuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finnish_cased_squad2_fi_5.2.0_3.0_1700182362083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finnish_cased_squad2_fi_5.2.0_3.0_1700182362083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_finnish_cased_squad2","fi") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_finnish_cased_squad2", "fi")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_finnish_cased_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fi|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/TurkuNLP/bert-base-finnish-cased-squad2
\ No newline at end of file

From 596dd67a9eb96f261a9ba75d58041d0d67f7ed8c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 07:53:57 +0700
Subject: [PATCH 317/408] Add model
 2023-11-17-bert_base_spanish_squad_spanish_tfm_4_question_answering_en

---
 ...uad_spanish_tfm_4_question_answering_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_squad_spanish_tfm_4_question_answering_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_squad_spanish_tfm_4_question_answering_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_squad_spanish_tfm_4_question_answering_en.md
new file mode 100644
index 00000000000000..a3ea9c2f8480e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_squad_spanish_tfm_4_question_answering_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_spanish_squad_spanish_tfm_4_question_answering BertForQuestionAnswering from JoelVIU
+author: John Snow Labs
+name: bert_base_spanish_squad_spanish_tfm_4_question_answering
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_squad_spanish_tfm_4_question_answering` is a English model originally trained by JoelVIU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_squad_spanish_tfm_4_question_answering_en_5.2.0_3.0_1700182364908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_squad_spanish_tfm_4_question_answering_en_5.2.0_3.0_1700182364908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_spanish_squad_spanish_tfm_4_question_answering","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_spanish_squad_spanish_tfm_4_question_answering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_spanish_squad_spanish_tfm_4_question_answering|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/JoelVIU/bert-base-spanish_squad_es-TFM_4-Question-Answering
\ No newline at end of file

From 0f0b5251fb23dbd89611d3fbfbfb93d0c856d8b5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:22:08 +0700
Subject: [PATCH 318/408] Add model
 2023-11-17-bert_base_uncased_finetuned_squad_v2_4_en

---
 ...rt_base_uncased_finetuned_squad_v2_4_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_4_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_4_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_4_en.md
new file mode 100644
index 00000000000000..1a302297de738c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_v2_4_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_v2_4 BertForQuestionAnswering from seviladiguzel
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_v2_4
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_v2_4` is a English model originally trained by seviladiguzel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_v2_4_en_5.2.0_3.0_1700184118361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_v2_4_en_5.2.0_3.0_1700184118361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_v2_4","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad_v2_4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_v2_4|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/seviladiguzel/bert-base-uncased-finetuned-squad_v2_4
\ No newline at end of file

From 983bda182d5b106ba25e7c894b0a586890ed4853 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:23:07 +0700
Subject: [PATCH 319/408] Add model
 2023-11-17-deepset_bert_base_uncased_squad2_trained_en

---
 ...set_bert_base_uncased_squad2_trained_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-deepset_bert_base_uncased_squad2_trained_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-deepset_bert_base_uncased_squad2_trained_en.md b/docs/_posts/ahmedlone127/2023-11-17-deepset_bert_base_uncased_squad2_trained_en.md
new file mode 100644
index 00000000000000..2a1c1eedcccce9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-deepset_bert_base_uncased_squad2_trained_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English deepset_bert_base_uncased_squad2_trained BertForQuestionAnswering from moska
+author: John Snow Labs
+name: deepset_bert_base_uncased_squad2_trained
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepset_bert_base_uncased_squad2_trained` is a English model originally trained by moska.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepset_bert_base_uncased_squad2_trained_en_5.2.0_3.0_1700184122622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepset_bert_base_uncased_squad2_trained_en_5.2.0_3.0_1700184122622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("deepset_bert_base_uncased_squad2_trained","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("deepset_bert_base_uncased_squad2_trained", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deepset_bert_base_uncased_squad2_trained|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/moska/deepset_bert-base-uncased-squad2_trained
\ No newline at end of file

From 7c1225093c30ecfa3fc773539759e7e0d23b12ee Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:24:08 +0700
Subject: [PATCH 320/408] Add model
 2023-11-17-bert_finetuned_squad_accelerate_zouhair1_en

---
 ..._finetuned_squad_accelerate_zouhair1_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_accelerate_zouhair1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_accelerate_zouhair1_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_accelerate_zouhair1_en.md
new file mode 100644
index 00000000000000..133312f8df4287
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_accelerate_zouhair1_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_accelerate_zouhair1 BertForQuestionAnswering from Zouhair1
+author: John Snow Labs
+name: bert_finetuned_squad_accelerate_zouhair1
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_zouhair1` is a English model originally trained by Zouhair1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_zouhair1_en_5.2.0_3.0_1700184122737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_zouhair1_en_5.2.0_3.0_1700184122737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_zouhair1","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_accelerate_zouhair1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_accelerate_zouhair1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Zouhair1/bert-finetuned-squad-accelerate
\ No newline at end of file

From 0646abcbe09379a7a28fae63c16d3eaaced126f8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:46:24 +0700
Subject: [PATCH 321/408] Add model
 2023-11-17-legal_document_question_answering_zh

---
 ...17-legal_document_question_answering_zh.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-legal_document_question_answering_zh.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-legal_document_question_answering_zh.md b/docs/_posts/ahmedlone127/2023-11-17-legal_document_question_answering_zh.md
new file mode 100644
index 00000000000000..34608015d4a6fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-legal_document_question_answering_zh.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Chinese legal_document_question_answering BertForQuestionAnswering from NchuNLP
+author: John Snow Labs
+name: legal_document_question_answering
+date: 2023-11-17
+tags: [bert, zh, open_source, question_answering, onnx]
+task: Question Answering
+language: zh
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_document_question_answering` is a Chinese model originally trained by NchuNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_document_question_answering_zh_5.2.0_3.0_1700185572714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_document_question_answering_zh_5.2.0_3.0_1700185572714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("legal_document_question_answering","zh") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("legal_document_question_answering", "zh")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_document_question_answering|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|zh|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/NchuNLP/Legal-Document-Question-Answering
\ No newline at end of file

From 78d4af720fd1c1024a473aabe45e0feb5d50d178 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:47:24 +0700
Subject: [PATCH 322/408] Add model
 2023-11-17-bert_finetuned_squad_sandeepmbm_en

---
 ...1-17-bert_finetuned_squad_sandeepmbm_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sandeepmbm_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sandeepmbm_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sandeepmbm_en.md
new file mode 100644
index 00000000000000..a7af70637ef648
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_sandeepmbm_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_sandeepmbm BertForQuestionAnswering from sandeepmbm
+author: John Snow Labs
+name: bert_finetuned_squad_sandeepmbm
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_sandeepmbm` is a English model originally trained by sandeepmbm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sandeepmbm_en_5.2.0_3.0_1700185572765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sandeepmbm_en_5.2.0_3.0_1700185572765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_sandeepmbm","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_sandeepmbm", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_sandeepmbm|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/sandeepmbm/bert-finetuned-squad
\ No newline at end of file

From 85c14b1f9ff7d7be83ea3751afa976fd22e7edc5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:48:24 +0700
Subject: [PATCH 323/408] Add model
 2023-11-17-bert_base_chinese_finetuned_qa_b8_en

---
 ...17-bert_base_chinese_finetuned_qa_b8_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_en.md
new file mode 100644
index 00000000000000..0f6cf3e8f2362b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_chinese_finetuned_qa_b8 BertForQuestionAnswering from sharkMeow
+author: John Snow Labs
+name: bert_base_chinese_finetuned_qa_b8
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_qa_b8` is a English model originally trained by sharkMeow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_qa_b8_en_5.2.0_3.0_1700185572697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_qa_b8_en_5.2.0_3.0_1700185572697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_chinese_finetuned_qa_b8","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_chinese_finetuned_qa_b8", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_chinese_finetuned_qa_b8|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/sharkMeow/bert-base-chinese-finetuned-QA-b8
\ No newline at end of file

From 1f7c93ea531dda831ff09865ffd37d77da700961 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 08:50:39 +0700
Subject: [PATCH 324/408] Add model 2023-11-17-heq_en

---
 docs/_posts/ahmedlone127/2023-11-17-heq_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-heq_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-heq_en.md b/docs/_posts/ahmedlone127/2023-11-17-heq_en.md
new file mode 100644
index 00000000000000..c9e2586ec4f874
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-heq_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English heq BertForQuestionAnswering from amirdnc
+author: John Snow Labs
+name: heq
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`heq` is a English model originally trained by amirdnc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/heq_en_5.2.0_3.0_1700185821460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/heq_en_5.2.0_3.0_1700185821460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("heq","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("heq", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|heq|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/amirdnc/HeQ
\ No newline at end of file

From fbe7ea31feaacc88cf513ff0b4043a9f09eb0791 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:05:30 +0700
Subject: [PATCH 325/408] Add model 2023-11-17-electra_qa_long_ko

---
 .../2023-11-17-electra_qa_long_ko.md          | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-electra_qa_long_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-electra_qa_long_ko.md b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_long_ko.md
new file mode 100644
index 00000000000000..a4801e86c8166c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_long_ko.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Korean ElectraForQuestionAnswering model (from sehandev)
+author: John Snow Labs
+name: electra_qa_long
+date: 2023-11-17
+tags: [ko, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `koelectra-long-qa` is a Korean model originally trained by `sehandev`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_long_ko_5.2.0_3.0_1700186722924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_long_ko_5.2.0_3.0_1700186722924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_long","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_long","ko") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.electra").predict("""내 이름은 무엇입니까?|||"제 이름은 클라라이고 저는 버클리에 살고 있습니다.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_long|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|419.4 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/sehandev/koelectra-long-qa
\ No newline at end of file

From 8f655a497d0d675c48cf793a0e927f0cd5ce9ecc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:06:59 +0700
Subject: [PATCH 326/408] Add model 2023-11-17-bert_finetuned_squad_tmatup_en

---
 ...23-11-17-bert_finetuned_squad_tmatup_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_tmatup_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_tmatup_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_tmatup_en.md
new file mode 100644
index 00000000000000..bdd3895bd1473b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_tmatup_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_tmatup BertForQuestionAnswering from tmatup
+author: John Snow Labs
+name: bert_finetuned_squad_tmatup
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_tmatup` is a English model originally trained by tmatup.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_tmatup_en_5.2.0_3.0_1700186812640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_tmatup_en_5.2.0_3.0_1700186812640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_tmatup","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_tmatup", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_tmatup|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/tmatup/bert-finetuned-squad
\ No newline at end of file

From 6eb59eb2952239f9b1ba9764b871d1c09832ddf8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:08:00 +0700
Subject: [PATCH 327/408] Add model
 2023-11-17-bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en

---
 ...panish_wwm_uncased_finetuned_qa_mlqa_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en.md
new file mode 100644
index 00000000000000..beb8ff8aa97c8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_spanish_wwm_uncased_finetuned_qa_mlqa BertForQuestionAnswering from dccuchile
+author: John Snow Labs
+name: bert_base_spanish_wwm_uncased_finetuned_qa_mlqa
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_uncased_finetuned_qa_mlqa` is a English model originally trained by dccuchile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en_5.2.0_3.0_1700186827331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_qa_mlqa_en_5.2.0_3.0_1700186827331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_spanish_wwm_uncased_finetuned_qa_mlqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_spanish_wwm_uncased_finetuned_qa_mlqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_spanish_wwm_uncased_finetuned_qa_mlqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased-finetuned-qa-mlqa
\ No newline at end of file

From 58f923fa22597e09be2251a40a3f89571b6e1cbd Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:09:00 +0700
Subject: [PATCH 328/408] Add model 2023-11-17-bert_10_en

---
 .../ahmedlone127/2023-11-17-bert_10_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_10_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_10_en.md
new file mode 100644
index 00000000000000..55ac32c1731f08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_10_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_10 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_10
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_10` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_10_en_5.2.0_3.0_1700186903229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_10_en_5.2.0_3.0_1700186903229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_10","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_10", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-10
\ No newline at end of file

From 98a188fa05eaf7618a2a248002f68f0228093058 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:11:07 +0700
Subject: [PATCH 329/408] Add model 2023-11-17-qa_persian_complete_en

---
 .../2023-11-17-qa_persian_complete_en.md      | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-qa_persian_complete_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-qa_persian_complete_en.md b/docs/_posts/ahmedlone127/2023-11-17-qa_persian_complete_en.md
new file mode 100644
index 00000000000000..9a6373c8174cfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-qa_persian_complete_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English qa_persian_complete BertForQuestionAnswering from AliBagherz
+author: John Snow Labs
+name: qa_persian_complete
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_persian_complete` is a English model originally trained by AliBagherz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_persian_complete_en_5.2.0_3.0_1700187055678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_persian_complete_en_5.2.0_3.0_1700187055678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_persian_complete","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("qa_persian_complete", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_persian_complete|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/AliBagherz/qa-persian-complete
\ No newline at end of file

From 9a2f1aab695da4ab44b8eeb24e3568e9b9ff3ec4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:28:50 +0700
Subject: [PATCH 330/408] Add model 2023-11-17-parsbert_finetuned_persianqa_en

---
 ...3-11-17-parsbert_finetuned_persianqa_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-parsbert_finetuned_persianqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-parsbert_finetuned_persianqa_en.md b/docs/_posts/ahmedlone127/2023-11-17-parsbert_finetuned_persianqa_en.md
new file mode 100644
index 00000000000000..ee527052b3c9bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-parsbert_finetuned_persianqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English parsbert_finetuned_persianqa BertForQuestionAnswering from marzinouri
+author: John Snow Labs
+name: parsbert_finetuned_persianqa
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_finetuned_persianqa` is a English model originally trained by marzinouri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/parsbert_finetuned_persianqa_en_5.2.0_3.0_1700188118419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_finetuned_persianqa_en_5.2.0_3.0_1700188118419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("parsbert_finetuned_persianqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("parsbert_finetuned_persianqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|parsbert_finetuned_persianqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|441.6 MB|
+
+## References
+
+https://huggingface.co/marzinouri/parsbert-finetuned-persianQA
\ No newline at end of file

From 4cdb73ad0e77b4a98f5a65d9e585f7dd1e69ea64 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:29:50 +0700
Subject: [PATCH 331/408] Add model
 2023-11-17-bert_base_spanish_wwm_cased_finetuned_quales_en

---
 ...e_spanish_wwm_cased_finetuned_quales_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_cased_finetuned_quales_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_cased_finetuned_quales_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_cased_finetuned_quales_en.md
new file mode 100644
index 00000000000000..2aab60e6740c8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_spanish_wwm_cased_finetuned_quales_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_spanish_wwm_cased_finetuned_quales BertForQuestionAnswering from luischir
+author: John Snow Labs
+name: bert_base_spanish_wwm_cased_finetuned_quales
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_quales` is a English model originally trained by luischir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_quales_en_5.2.0_3.0_1700188118106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_quales_en_5.2.0_3.0_1700188118106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_spanish_wwm_cased_finetuned_quales","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_spanish_wwm_cased_finetuned_quales", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_spanish_wwm_cased_finetuned_quales|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/luischir/bert-base-spanish-wwm-cased-finetuned-quales
\ No newline at end of file

From 9629ec980016340860cd9cd9d71a6670c6af9f3d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:34:02 +0700
Subject: [PATCH 332/408] Add model
 2023-11-17-ekattorbert_multilingual_finetuned_squad_v2_xx

---
 ...bert_multilingual_finetuned_squad_v2_xx.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-ekattorbert_multilingual_finetuned_squad_v2_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-ekattorbert_multilingual_finetuned_squad_v2_xx.md b/docs/_posts/ahmedlone127/2023-11-17-ekattorbert_multilingual_finetuned_squad_v2_xx.md
new file mode 100644
index 00000000000000..3351b705271ae5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-ekattorbert_multilingual_finetuned_squad_v2_xx.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Multilingual ekattorbert_multilingual_finetuned_squad_v2 BertForQuestionAnswering from shawmoon
+author: John Snow Labs
+name: ekattorbert_multilingual_finetuned_squad_v2
+date: 2023-11-17
+tags: [bert, xx, open_source, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ekattorbert_multilingual_finetuned_squad_v2` is a Multilingual model originally trained by shawmoon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ekattorbert_multilingual_finetuned_squad_v2_xx_5.2.0_3.0_1700188428485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ekattorbert_multilingual_finetuned_squad_v2_xx_5.2.0_3.0_1700188428485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ekattorbert_multilingual_finetuned_squad_v2","xx") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ekattorbert_multilingual_finetuned_squad_v2", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ekattorbert_multilingual_finetuned_squad_v2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/shawmoon/EkattorBert-multilingual-finetuned-squad_v2
\ No newline at end of file

From 4545ac42e2fcb2120110c4e313ae53da84431420 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:35:03 +0700
Subject: [PATCH 333/408] Add model 2023-11-17-bert_base_mrqa_en

---
 .../2023-11-17-bert_base_mrqa_en.md           | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_mrqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_mrqa_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_mrqa_en.md
new file mode 100644
index 00000000000000..ea74797a3abe1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_mrqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_mrqa BertForQuestionAnswering from VMware
+author: John Snow Labs
+name: bert_base_mrqa
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_mrqa` is a English model originally trained by VMware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mrqa_en_5.2.0_3.0_1700188428332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mrqa_en_5.2.0_3.0_1700188428332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_mrqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_mrqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_mrqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/VMware/bert-base-mrqa
\ No newline at end of file

From fe46bb800dbc95e2e24e58daca3223088663a5b9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:36:03 +0700
Subject: [PATCH 334/408] Add model 2023-11-17-electra_qa_slp_en

---
 .../2023-11-17-electra_qa_slp_en.md           | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-electra_qa_slp_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-electra_qa_slp_en.md b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_slp_en.md
new file mode 100644
index 00000000000000..7fb1257bdac384
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_slp_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from rowan1224)
+author: John Snow Labs
+name: electra_qa_slp
+date: 2023-11-17
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-slp` is a English model originally trained by `rowan1224`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_slp_en_5.2.0_3.0_1700188524329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_slp_en_5.2.0_3.0_1700188524329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_slp","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_slp","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.electra.by_rowan1224").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_slp|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/rowan1224/electra-slp
\ No newline at end of file

From 87a7382f4df064604ac98253ddb1df43b22d1ff1 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:46:37 +0700
Subject: [PATCH 335/408] Add model
 2023-11-17-bert_finetuned_squad_zhangh795_en

---
 ...11-17-bert_finetuned_squad_zhangh795_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_zhangh795_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_zhangh795_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_zhangh795_en.md
new file mode 100644
index 00000000000000..aaaec8da8f099a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_zhangh795_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_zhangh795 BertForQuestionAnswering from ZhangH795
+author: John Snow Labs
+name: bert_finetuned_squad_zhangh795
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_zhangh795` is a English model originally trained by ZhangH795.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_zhangh795_en_5.2.0_3.0_1700189186725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_zhangh795_en_5.2.0_3.0_1700189186725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_zhangh795","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_zhangh795", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_zhangh795|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ZhangH795/bert-finetuned-squad
\ No newline at end of file

From bbe85262e585404f84adfa76417663aca23ad152 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:47:38 +0700
Subject: [PATCH 336/408] Add model 2023-11-17-clibert_20_en

---
 .../ahmedlone127/2023-11-17-clibert_20_en.md  | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-clibert_20_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-clibert_20_en.md b/docs/_posts/ahmedlone127/2023-11-17-clibert_20_en.md
new file mode 100644
index 00000000000000..8dae42f47aa6b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-clibert_20_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English clibert_20 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: clibert_20
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clibert_20` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clibert_20_en_5.2.0_3.0_1700189186705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clibert_20_en_5.2.0_3.0_1700189186705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("clibert_20","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("clibert_20", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clibert_20|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/hung200504/CliBert-20
\ No newline at end of file

From ab5d1cb81887a4c394b2f04c10e8eb6267329661 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:52:56 +0700
Subject: [PATCH 337/408] Add model 2023-11-17-energybert_finetuned_squad_en

---
 ...023-11-17-energybert_finetuned_squad_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-energybert_finetuned_squad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-energybert_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2023-11-17-energybert_finetuned_squad_en.md
new file mode 100644
index 00000000000000..125dae564626ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-energybert_finetuned_squad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English energybert_finetuned_squad BertForQuestionAnswering from HongyangLi
+author: John Snow Labs
+name: energybert_finetuned_squad
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`energybert_finetuned_squad` is a English model originally trained by HongyangLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/energybert_finetuned_squad_en_5.2.0_3.0_1700189569320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/energybert_finetuned_squad_en_5.2.0_3.0_1700189569320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("energybert_finetuned_squad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("energybert_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|energybert_finetuned_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/HongyangLi/energybert-finetuned-squad
\ No newline at end of file

From 16dc1eaefbdacaf720334ceb996816f2362efe45 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 09:53:57 +0700
Subject: [PATCH 338/408] Add model
 2023-11-17-electra_qa_small_discriminator_finetuned_squad_1_en

---
 ...mall_discriminator_finetuned_squad_1_en.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_discriminator_finetuned_squad_1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_discriminator_finetuned_squad_1_en.md b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_discriminator_finetuned_squad_1_en.md
new file mode 100644
index 00000000000000..d1478e3f608fb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_discriminator_finetuned_squad_1_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from bdickson) Version-1
+author: John Snow Labs
+name: electra_qa_small_discriminator_finetuned_squad_1
+date: 2023-11-17
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-small-discriminator-finetuned-squad` is a English model originally trained by `bdickson`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_small_discriminator_finetuned_squad_1_en_5.2.0_3.0_1700189577951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_small_discriminator_finetuned_squad_1_en_5.2.0_3.0_1700189577951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_small_discriminator_finetuned_squad_1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_small_discriminator_finetuned_squad_1","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.small.by_bdickson").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_small_discriminator_finetuned_squad_1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|50.8 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/bdickson/electra-small-discriminator-finetuned-squad
\ No newline at end of file

From 0cd3936d6f1a07eb85bf8f4d94959b9bfda376be Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:05:41 +0700
Subject: [PATCH 339/408] Add model
 2023-11-17-bert_finetuned_squad_johnxiaxj_en

---
 ...11-17-bert_finetuned_squad_johnxiaxj_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_johnxiaxj_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_johnxiaxj_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_johnxiaxj_en.md
new file mode 100644
index 00000000000000..13de5a58a0bc65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_johnxiaxj_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_johnxiaxj BertForQuestionAnswering from JohnXiaXJ
+author: John Snow Labs
+name: bert_finetuned_squad_johnxiaxj
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_johnxiaxj` is a English model originally trained by JohnXiaXJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_johnxiaxj_en_5.2.0_3.0_1700190329198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_johnxiaxj_en_5.2.0_3.0_1700190329198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_johnxiaxj","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_johnxiaxj", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_johnxiaxj|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/JohnXiaXJ/bert-finetuned-squad
\ No newline at end of file

From 84f524928bd3523d7d7b7ddf29e0c738d987d4c8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:06:41 +0700
Subject: [PATCH 340/408] Add model
 2023-11-17-bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en

---
 ..._0_southern_sotho_true_fh_false_hs_0_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..da90423292bb70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.2.0_3.0_1700190329192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.2.0_3.0_1700190329192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_10_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-10.0-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file

From b87b6ad8d811f08ed2bd4c6fb2d8983ca5c33760 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:07:41 +0700
Subject: [PATCH 341/408] Add model
 2023-11-17-electra_qa_small_v3_finetuned_korquad_ko

---
 ...lectra_qa_small_v3_finetuned_korquad_ko.md | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_v3_finetuned_korquad_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_v3_finetuned_korquad_ko.md b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_v3_finetuned_korquad_ko.md
new file mode 100644
index 00000000000000..70e7b2e5e9b69a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-electra_qa_small_v3_finetuned_korquad_ko.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: Korean ElectraForQuestionAnswering Small model (from monologg) Version-3
+author: John Snow Labs
+name: electra_qa_small_v3_finetuned_korquad
+date: 2023-11-17
+tags: [ko, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `koelectra-small-v3-finetuned-korquad` is a Korean model originally trained by `monologg`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electra_qa_small_v3_finetuned_korquad_ko_5.2.0_3.0_1700190429493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_small_v3_finetuned_korquad_ko_5.2.0_3.0_1700190429493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_small_v3_finetuned_korquad","ko") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_small_v3_finetuned_korquad","ko") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("내 이름은 무엇입니까?", "제 이름은 클라라이고 저는 버클리에 살고 있습니다.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("ko.answer_question.korquad.electra.small").predict("""내 이름은 무엇입니까?|||"제 이름은 클라라이고 저는 버클리에 살고 있습니다.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_small_v3_finetuned_korquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|53.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/monologg/koelectra-small-v3-finetuned-korquad
\ No newline at end of file

From 06711c7592b9898fd559d52ecf1c0dfda36eaac5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:08:42 +0700
Subject: [PATCH 342/408] Add model 2023-11-17-bert_finetuned_squad_yifanpan_en

---
 ...-11-17-bert_finetuned_squad_yifanpan_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_yifanpan_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_yifanpan_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_yifanpan_en.md
new file mode 100644
index 00000000000000..842fae1c5bf445
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_yifanpan_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_yifanpan BertForQuestionAnswering from YifanPan
+author: John Snow Labs
+name: bert_finetuned_squad_yifanpan
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_yifanpan` is a English model originally trained by YifanPan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_yifanpan_en_5.2.0_3.0_1700190500124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_yifanpan_en_5.2.0_3.0_1700190500124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_yifanpan","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_yifanpan", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_yifanpan|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/YifanPan/bert-finetuned-squad
\ No newline at end of file

From a51322235b453ccaabfc8072e327cf3247c46291 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:12:06 +0700
Subject: [PATCH 343/408] Add model 2023-11-17-wspalign_ft_kftt_en

---
 .../2023-11-17-wspalign_ft_kftt_en.md         | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-wspalign_ft_kftt_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-wspalign_ft_kftt_en.md b/docs/_posts/ahmedlone127/2023-11-17-wspalign_ft_kftt_en.md
new file mode 100644
index 00000000000000..bc795cde57056c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-wspalign_ft_kftt_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English wspalign_ft_kftt BertForQuestionAnswering from qiyuw
+author: John Snow Labs
+name: wspalign_ft_kftt
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wspalign_ft_kftt` is a English model originally trained by qiyuw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wspalign_ft_kftt_en_5.2.0_3.0_1700190715563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wspalign_ft_kftt_en_5.2.0_3.0_1700190715563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("wspalign_ft_kftt","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("wspalign_ft_kftt", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wspalign_ft_kftt|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/qiyuw/WSPAlign-ft-kftt
\ No newline at end of file

From 702be5130af22ec83f4ee14db34258e62f45ff3e Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:26:53 +0700
Subject: [PATCH 344/408] Add model 2023-11-17-all_minilm_l12_v2_qa_english_en

---
 ...3-11-17-all_minilm_l12_v2_qa_english_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-all_minilm_l12_v2_qa_english_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-all_minilm_l12_v2_qa_english_en.md b/docs/_posts/ahmedlone127/2023-11-17-all_minilm_l12_v2_qa_english_en.md
new file mode 100644
index 00000000000000..82fe1c5af082c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-all_minilm_l12_v2_qa_english_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English all_minilm_l12_v2_qa_english BertForQuestionAnswering from LLukas22
+author: John Snow Labs
+name: all_minilm_l12_v2_qa_english
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l12_v2_qa_english` is a English model originally trained by LLukas22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l12_v2_qa_english_en_5.2.0_3.0_1700191610001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l12_v2_qa_english_en_5.2.0_3.0_1700191610001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("all_minilm_l12_v2_qa_english","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("all_minilm_l12_v2_qa_english", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l12_v2_qa_english|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|124.1 MB|
+
+## References
+
+https://huggingface.co/LLukas22/all-MiniLM-L12-v2-qa-en
\ No newline at end of file

From 45aea1aabe930097ba4602757c5f52e64a9f8af7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:27:53 +0700
Subject: [PATCH 345/408] Add model 2023-11-17-kanuri_bert_qa_en

---
 .../2023-11-17-kanuri_bert_qa_en.md           | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-kanuri_bert_qa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-kanuri_bert_qa_en.md b/docs/_posts/ahmedlone127/2023-11-17-kanuri_bert_qa_en.md
new file mode 100644
index 00000000000000..bbd68b9f74aa3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-kanuri_bert_qa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English kanuri_bert_qa BertForQuestionAnswering from J1won7
+author: John Snow Labs
+name: kanuri_bert_qa
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kanuri_bert_qa` is a English model originally trained by J1won7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kanuri_bert_qa_en_5.2.0_3.0_1700191610338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kanuri_bert_qa_en_5.2.0_3.0_1700191610338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("kanuri_bert_qa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("kanuri_bert_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kanuri_bert_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|367.3 MB|
+
+## References
+
+https://huggingface.co/J1won7/kr-bert-qa
\ No newline at end of file

From 5cbce4f07355b158348ed41b95d148aacce5d140 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:28:53 +0700
Subject: [PATCH 346/408] Add model
 2023-11-17-bert_finetuned_squad_shabdansh01_en

---
 ...-17-bert_finetuned_squad_shabdansh01_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_shabdansh01_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_shabdansh01_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_shabdansh01_en.md
new file mode 100644
index 00000000000000..134ecd11622fe0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_shabdansh01_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_shabdansh01 BertForQuestionAnswering from Shabdansh01
+author: John Snow Labs
+name: bert_finetuned_squad_shabdansh01
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_shabdansh01` is a English model originally trained by Shabdansh01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_shabdansh01_en_5.2.0_3.0_1700191612352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_shabdansh01_en_5.2.0_3.0_1700191612352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_shabdansh01","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_shabdansh01", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_shabdansh01|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Shabdansh01/bert-finetuned-squad
\ No newline at end of file

From b6b3e806aaaf8edcb920c9d5f20b95b7751f64ab Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:29:53 +0700
Subject: [PATCH 347/408] Add model
 2023-11-17-darijabert_finetuned_arabic_squad_ar

---
 ...17-darijabert_finetuned_arabic_squad_ar.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-darijabert_finetuned_arabic_squad_ar.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-darijabert_finetuned_arabic_squad_ar.md b/docs/_posts/ahmedlone127/2023-11-17-darijabert_finetuned_arabic_squad_ar.md
new file mode 100644
index 00000000000000..e669094bacae6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-darijabert_finetuned_arabic_squad_ar.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Arabic darijabert_finetuned_arabic_squad BertForQuestionAnswering from JasperV13
+author: John Snow Labs
+name: darijabert_finetuned_arabic_squad
+date: 2023-11-17
+tags: [bert, ar, open_source, question_answering, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darijabert_finetuned_arabic_squad` is a Arabic model originally trained by JasperV13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darijabert_finetuned_arabic_squad_ar_5.2.0_3.0_1700191737908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darijabert_finetuned_arabic_squad_ar_5.2.0_3.0_1700191737908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("darijabert_finetuned_arabic_squad","ar") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("darijabert_finetuned_arabic_squad", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darijabert_finetuned_arabic_squad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|551.5 MB|
+
+## References
+
+https://huggingface.co/JasperV13/DarijaBERT-finetuned-Arabic-SQuAD
\ No newline at end of file

From f3d3078f229a57ce5d5038995aad3b6d9aa1123f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:30:54 +0700
Subject: [PATCH 348/408] Add model
 2023-11-17-tiny_random_bertforquestionanswering_en

---
 ...tiny_random_bertforquestionanswering_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-tiny_random_bertforquestionanswering_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-tiny_random_bertforquestionanswering_en.md b/docs/_posts/ahmedlone127/2023-11-17-tiny_random_bertforquestionanswering_en.md
new file mode 100644
index 00000000000000..02cecd80efd11a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-tiny_random_bertforquestionanswering_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English tiny_random_bertforquestionanswering BertForQuestionAnswering from hf-tiny-model-private
+author: John Snow Labs
+name: tiny_random_bertforquestionanswering
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_bertforquestionanswering` is a English model originally trained by hf-tiny-model-private.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_bertforquestionanswering_en_5.2.0_3.0_1700191644425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_bertforquestionanswering_en_5.2.0_3.0_1700191644425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("tiny_random_bertforquestionanswering","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("tiny_random_bertforquestionanswering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_bertforquestionanswering|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|346.4 KB|
+
+## References
+
+https://huggingface.co/hf-tiny-model-private/tiny-random-BertForQuestionAnswering
\ No newline at end of file

From d301ddffe326948c38176287e2afa54f953fe5e2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:52:57 +0700
Subject: [PATCH 349/408] Add model 2023-11-17-bert_finetuned_squad_aaroosh_en

---
 ...3-11-17-bert_finetuned_squad_aaroosh_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_aaroosh_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_aaroosh_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_aaroosh_en.md
new file mode 100644
index 00000000000000..a7ff18a618157b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_aaroosh_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_aaroosh BertForQuestionAnswering from Aaroosh
+author: John Snow Labs
+name: bert_finetuned_squad_aaroosh
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_aaroosh` is a English model originally trained by Aaroosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_aaroosh_en_5.2.0_3.0_1700193166034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_aaroosh_en_5.2.0_3.0_1700193166034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_aaroosh","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_aaroosh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_aaroosh|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Aaroosh/bert-finetuned-squad
\ No newline at end of file

From 847849a09c9db9a6d6b3127cc244621dd80ddc4b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:53:57 +0700
Subject: [PATCH 350/408] Add model 2023-11-17-bert_finetuned_squad_lexie79_en

---
 ...3-11-17-bert_finetuned_squad_lexie79_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_lexie79_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_lexie79_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_lexie79_en.md
new file mode 100644
index 00000000000000..75c4f16a241ac2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_lexie79_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_lexie79 BertForQuestionAnswering from Lexie79
+author: John Snow Labs
+name: bert_finetuned_squad_lexie79
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_lexie79` is a English model originally trained by Lexie79.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_lexie79_en_5.2.0_3.0_1700193166028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_lexie79_en_5.2.0_3.0_1700193166028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_lexie79","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_lexie79", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_lexie79|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Lexie79/bert-finetuned-squad
\ No newline at end of file

From 7f0132cdf7d818bd66eac65f3fdde7dc5dc2ba28 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:54:57 +0700
Subject: [PATCH 351/408] Add model 2023-11-17-bert_finetuned_squad_catlord_en

---
 ...3-11-17-bert_finetuned_squad_catlord_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_catlord_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_catlord_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_catlord_en.md
new file mode 100644
index 00000000000000..33ce553946cb60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_catlord_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_catlord BertForQuestionAnswering from catlord
+author: John Snow Labs
+name: bert_finetuned_squad_catlord
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_catlord` is a English model originally trained by catlord.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_catlord_en_5.2.0_3.0_1700193166013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_catlord_en_5.2.0_3.0_1700193166013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_catlord","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_catlord", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_catlord|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/catlord/bert-finetuned-squad
\ No newline at end of file

From 092071fab84ffcd8ca920089c5cc1b27a388ec34 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:55:58 +0700
Subject: [PATCH 352/408] Add model 2023-11-17-mbert_squadv2_en

---
 .../2023-11-17-mbert_squadv2_en.md            | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-mbert_squadv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-mbert_squadv2_en.md b/docs/_posts/ahmedlone127/2023-11-17-mbert_squadv2_en.md
new file mode 100644
index 00000000000000..7276576161a12b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-mbert_squadv2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English mbert_squadv2 BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: mbert_squadv2
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_squadv2` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_squadv2_en_5.2.0_3.0_1700193166276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_squadv2_en_5.2.0_3.0_1700193166276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mbert_squadv2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("mbert_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/mbert-squadv2
\ No newline at end of file

From e0187ef0028e0be9e6cd4d8cce98e1cf56470b29 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 10:56:58 +0700
Subject: [PATCH 353/408] Add model 2023-11-17-dictabert_heq_he

---
 .../2023-11-17-dictabert_heq_he.md            | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-dictabert_heq_he.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-dictabert_heq_he.md b/docs/_posts/ahmedlone127/2023-11-17-dictabert_heq_he.md
new file mode 100644
index 00000000000000..20e7fe11625f57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-dictabert_heq_he.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Hebrew dictabert_heq BertForQuestionAnswering from dicta-il
+author: John Snow Labs
+name: dictabert_heq
+date: 2023-11-17
+tags: [bert, he, open_source, question_answering, onnx]
+task: Question Answering
+language: he
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dictabert_heq` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dictabert_heq_he_5.2.0_3.0_1700193363237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dictabert_heq_he_5.2.0_3.0_1700193363237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("dictabert_heq","he") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("dictabert_heq", "he")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dictabert_heq|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|he|
+|Size:|645.0 MB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert-heq
\ No newline at end of file

From 5ecf30ed2e051abc8dd96b71c7c77a5743e5c3b8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:12:42 +0700
Subject: [PATCH 354/408] Add model
 2023-11-17-question_answering_bert_base_cased_squad2_en

---
 ...ion_answering_bert_base_cased_squad2_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-question_answering_bert_base_cased_squad2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-question_answering_bert_base_cased_squad2_en.md b/docs/_posts/ahmedlone127/2023-11-17-question_answering_bert_base_cased_squad2_en.md
new file mode 100644
index 00000000000000..729eb058bdc2e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-question_answering_bert_base_cased_squad2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English question_answering_bert_base_cased_squad2 BertForQuestionAnswering from TunahanGokcimen
+author: John Snow Labs
+name: question_answering_bert_base_cased_squad2
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_bert_base_cased_squad2` is a English model originally trained by TunahanGokcimen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_bert_base_cased_squad2_en_5.2.0_3.0_1700194348732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_bert_base_cased_squad2_en_5.2.0_3.0_1700194348732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("question_answering_bert_base_cased_squad2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("question_answering_bert_base_cased_squad2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_bert_base_cased_squad2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/TunahanGokcimen/Question-Answering-Bert-base-cased-squad2
\ No newline at end of file

From 183b3921cc22f5a07d2974e5a7e80b95b942ffc5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:13:41 +0700
Subject: [PATCH 355/408] Add model
 2023-11-17-bert_finetuned_squad_marcuslee_en

---
 ...11-17-bert_finetuned_squad_marcuslee_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcuslee_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcuslee_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcuslee_en.md
new file mode 100644
index 00000000000000..f50f533ebc36a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcuslee_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_marcuslee BertForQuestionAnswering from MarcusLee
+author: John Snow Labs
+name: bert_finetuned_squad_marcuslee
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_marcuslee` is a English model originally trained by MarcusLee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marcuslee_en_5.2.0_3.0_1700194348722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marcuslee_en_5.2.0_3.0_1700194348722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_marcuslee","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_marcuslee", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_marcuslee|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/MarcusLee/bert-finetuned-squad
\ No newline at end of file

From 1ebfe3a97a862bcc6ef13d963fb50c5eaaaa1fca Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:14:42 +0700
Subject: [PATCH 356/408] Add model 2023-11-17-bert_squad_chatbot_aai_en

---
 .../2023-11-17-bert_squad_chatbot_aai_en.md   | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_squad_chatbot_aai_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_squad_chatbot_aai_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_squad_chatbot_aai_en.md
new file mode 100644
index 00000000000000..5a2ddb30732835
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_squad_chatbot_aai_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_squad_chatbot_aai BertForQuestionAnswering from tmcgirr
+author: John Snow Labs
+name: bert_squad_chatbot_aai
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_chatbot_aai` is a English model originally trained by tmcgirr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_chatbot_aai_en_5.2.0_3.0_1700194433336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_chatbot_aai_en_5.2.0_3.0_1700194433336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_squad_chatbot_aai","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_squad_chatbot_aai", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_chatbot_aai|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/tmcgirr/BERT-squad-chatbot-AAI
\ No newline at end of file

From 5c910c0dd94829aaa016c5855639d1b6ea494279 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:15:42 +0700
Subject: [PATCH 357/408] Add model 2023-11-17-matscibert_qa_en

---
 .../2023-11-17-matscibert_qa_en.md            | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-matscibert_qa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-matscibert_qa_en.md b/docs/_posts/ahmedlone127/2023-11-17-matscibert_qa_en.md
new file mode 100644
index 00000000000000..2bca4bde55aaa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-matscibert_qa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English matscibert_qa BertForQuestionAnswering from vrx2
+author: John Snow Labs
+name: matscibert_qa
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`matscibert_qa` is a English model originally trained by vrx2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/matscibert_qa_en_5.2.0_3.0_1700194352540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/matscibert_qa_en_5.2.0_3.0_1700194352540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("matscibert_qa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("matscibert_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|matscibert_qa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/vrx2/matscibert-QA
\ No newline at end of file

From 7ab8f7d802e57f9353a9ca28e2e30d044ab3e528 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:16:42 +0700
Subject: [PATCH 358/408] Add model
 2023-11-17-bert_finetuned_squad_jfarmerphd_en

---
 ...1-17-bert_finetuned_squad_jfarmerphd_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jfarmerphd_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jfarmerphd_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jfarmerphd_en.md
new file mode 100644
index 00000000000000..99a3445ed5a40e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jfarmerphd_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_jfarmerphd BertForQuestionAnswering from jfarmerphd
+author: John Snow Labs
+name: bert_finetuned_squad_jfarmerphd
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jfarmerphd` is a English model originally trained by jfarmerphd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jfarmerphd_en_5.2.0_3.0_1700194348728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jfarmerphd_en_5.2.0_3.0_1700194348728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jfarmerphd","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_jfarmerphd", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jfarmerphd|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/jfarmerphd/bert-finetuned-squad
\ No newline at end of file

From 47add85f542affacf162597e722a5c41cd0a25c4 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:33:57 +0700
Subject: [PATCH 359/408] Add model
 2023-11-17-bert_finetuned_squad_ihfaudsip_en

---
 ...11-17-bert_finetuned_squad_ihfaudsip_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ihfaudsip_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ihfaudsip_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ihfaudsip_en.md
new file mode 100644
index 00000000000000..256d8f2e2c8d24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ihfaudsip_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_ihfaudsip BertForQuestionAnswering from ihfaudsip
+author: John Snow Labs
+name: bert_finetuned_squad_ihfaudsip
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ihfaudsip` is a English model originally trained by ihfaudsip.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ihfaudsip_en_5.2.0_3.0_1700195630435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ihfaudsip_en_5.2.0_3.0_1700195630435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ihfaudsip","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_ihfaudsip", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ihfaudsip|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ihfaudsip/bert-finetuned-squad
\ No newline at end of file

From 7a6d1000d86d55ffe014e570e2263d0ffdb3244b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:37:53 +0700
Subject: [PATCH 360/408] Add model 2023-11-17-bert_finetuned_squad_heheshu_en

---
 ...3-11-17-bert_finetuned_squad_heheshu_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_heheshu_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_heheshu_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_heheshu_en.md
new file mode 100644
index 00000000000000..599f39e871e462
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_heheshu_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_heheshu BertForQuestionAnswering from heheshu
+author: John Snow Labs
+name: bert_finetuned_squad_heheshu
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_heheshu` is a English model originally trained by heheshu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_heheshu_en_5.2.0_3.0_1700195864033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_heheshu_en_5.2.0_3.0_1700195864033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_heheshu","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_heheshu", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_heheshu|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/heheshu/bert-finetuned-squad
\ No newline at end of file

From a1554e243e4cdedcb59bdb5b6a6365dc090eac17 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:38:54 +0700
Subject: [PATCH 361/408] Add model 2023-11-17-test_bert_3_en

---
 .../ahmedlone127/2023-11-17-test_bert_3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-test_bert_3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-test_bert_3_en.md b/docs/_posts/ahmedlone127/2023-11-17-test_bert_3_en.md
new file mode 100644
index 00000000000000..e7d99a11b1ab4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-test_bert_3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English test_bert_3 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: test_bert_3
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_bert_3` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_bert_3_en_5.2.0_3.0_1700195866022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_bert_3_en_5.2.0_3.0_1700195866022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("test_bert_3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("test_bert_3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_bert_3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/hung200504/test-bert-3
\ No newline at end of file

From c91959f587229cd697e15b912230cfc33c9fd9a2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:39:54 +0700
Subject: [PATCH 362/408] Add model 2023-11-17-bert_finetuned_on_nq_short_en

---
 ...023-11-17-bert_finetuned_on_nq_short_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_on_nq_short_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_on_nq_short_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_on_nq_short_en.md
new file mode 100644
index 00000000000000..4c2b7aef997cbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_on_nq_short_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_on_nq_short BertForQuestionAnswering from eibakke
+author: John Snow Labs
+name: bert_finetuned_on_nq_short
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_on_nq_short` is a English model originally trained by eibakke.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_on_nq_short_en_5.2.0_3.0_1700195868532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_on_nq_short_en_5.2.0_3.0_1700195868532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_on_nq_short","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_on_nq_short", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_on_nq_short|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/eibakke/bert-finetuned-on-nq-short
\ No newline at end of file

From cdcb2842df262140e45674684883cccfb562fee7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:50:10 +0700
Subject: [PATCH 363/408] Add model 2023-11-17-bert_21_en

---
 .../ahmedlone127/2023-11-17-bert_21_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_21_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_21_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_21_en.md
new file mode 100644
index 00000000000000..73c474eaf841dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_21_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_21 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_21
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_21` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_21_en_5.2.0_3.0_1700196602657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_21_en_5.2.0_3.0_1700196602657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_21","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_21", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_21|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-21
\ No newline at end of file

From 5131d45a4d7cca0a6e3cb6d3a71df7ae1ed956e0 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 11:52:51 +0700
Subject: [PATCH 364/408] Add model 2023-11-17-polaris_bert_0000_en

---
 .../2023-11-17-polaris_bert_0000_en.md        | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-polaris_bert_0000_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-polaris_bert_0000_en.md b/docs/_posts/ahmedlone127/2023-11-17-polaris_bert_0000_en.md
new file mode 100644
index 00000000000000..dd4f53c4e365e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-polaris_bert_0000_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English polaris_bert_0000 BertForQuestionAnswering from logoyazilim
+author: John Snow Labs
+name: polaris_bert_0000
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`polaris_bert_0000` is a English model originally trained by logoyazilim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/polaris_bert_0000_en_5.2.0_3.0_1700196764592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/polaris_bert_0000_en_5.2.0_3.0_1700196764592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("polaris_bert_0000","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("polaris_bert_0000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|polaris_bert_0000|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.2 MB|
+
+## References
+
+https://huggingface.co/logoyazilim/polaris_bert_0000
\ No newline at end of file

From 5b7bc9bc47d98dfb0418ee11733e9412b6e71675 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:03:35 +0700
Subject: [PATCH 365/408] Add model
 2023-11-17-bert_finetuned_squad_marcowong02_en

---
 ...-17-bert_finetuned_squad_marcowong02_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcowong02_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcowong02_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcowong02_en.md
new file mode 100644
index 00000000000000..fa488014fb5b68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_marcowong02_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_marcowong02 BertForQuestionAnswering from marcowong02
+author: John Snow Labs
+name: bert_finetuned_squad_marcowong02
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_marcowong02` is a English model originally trained by marcowong02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marcowong02_en_5.2.0_3.0_1700197403032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marcowong02_en_5.2.0_3.0_1700197403032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_marcowong02","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_marcowong02", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_marcowong02|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/marcowong02/bert-finetuned-squad
\ No newline at end of file

From 25fb424f98321fb1b1d8c4a0abedc18f7bb010db Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:04:35 +0700
Subject: [PATCH 366/408] Add model 2023-11-17-bert_finetuned_squad_krolis_en

---
 ...23-11-17-bert_finetuned_squad_krolis_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_krolis_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_krolis_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_krolis_en.md
new file mode 100644
index 00000000000000..6d347ecffab52a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_krolis_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_krolis BertForQuestionAnswering from krolis
+author: John Snow Labs
+name: bert_finetuned_squad_krolis
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_krolis` is a English model originally trained by krolis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_krolis_en_5.2.0_3.0_1700197403017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_krolis_en_5.2.0_3.0_1700197403017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_krolis","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_krolis", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_krolis|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/krolis/bert-finetuned-squad
\ No newline at end of file

From d38566f280f1887e197644d472adc3253de0515b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:17:16 +0700
Subject: [PATCH 367/408] Add model
 2023-11-17-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en

---
 ...model_for_common_downstream_tasks_v3_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en.md b/docs/_posts/ahmedlone127/2023-11-17-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en.md
new file mode 100644
index 00000000000000..ef6eef9c9456bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3 BertForQuestionAnswering from Tural
+author: John Snow Labs
+name: how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3` is a English model originally trained by Tural.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en_5.2.0_3.0_1700198227946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3_en_5.2.0_3.0_1700198227946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v3|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Tural/How_to_fine-tune_a_model_for_common_downstream_tasks_V3
\ No newline at end of file

From 704c24a66be53c129580281debba28f1b3713aac Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:28:29 +0700
Subject: [PATCH 368/408] Add model
 2023-11-17-bert_finetuned_squad_nightlighttw_en

---
 ...17-bert_finetuned_squad_nightlighttw_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_nightlighttw_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_nightlighttw_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_nightlighttw_en.md
new file mode 100644
index 00000000000000..b8681590632853
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_nightlighttw_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_nightlighttw BertForQuestionAnswering from nightlighttw
+author: John Snow Labs
+name: bert_finetuned_squad_nightlighttw
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_nightlighttw` is a English model originally trained by nightlighttw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_nightlighttw_en_5.2.0_3.0_1700198902920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_nightlighttw_en_5.2.0_3.0_1700198902920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_nightlighttw","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_nightlighttw", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_nightlighttw|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/nightlighttw/bert-finetuned-squad
\ No newline at end of file

From 7d392497b7479a32bf6eea6e6f2b325293c3d80c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:31:45 +0700
Subject: [PATCH 369/408] Add model
 2023-11-17-bert_base_uncased_finetuned_squad_harrynewcomb_en

---
 ...uncased_finetuned_squad_harrynewcomb_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_harrynewcomb_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_harrynewcomb_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_harrynewcomb_en.md
new file mode 100644
index 00000000000000..9f88ae6bf93643
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_harrynewcomb_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_harrynewcomb BertForQuestionAnswering from HarryNewcomb
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_harrynewcomb
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_harrynewcomb` is a English model originally trained by HarryNewcomb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_harrynewcomb_en_5.2.0_3.0_1700199098678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_harrynewcomb_en_5.2.0_3.0_1700199098678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_harrynewcomb","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad_harrynewcomb", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_harrynewcomb|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/HarryNewcomb/bert-base-uncased-finetuned-squad
\ No newline at end of file

From 3e8c8ee70fd42ac626ab5a15c2e11ca205fe03f6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:37:12 +0700
Subject: [PATCH 370/408] Add model
 2023-11-17-bert_base_uncased_finetuned_squad_badokorach_en

---
 ...e_uncased_finetuned_squad_badokorach_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_badokorach_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_badokorach_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_badokorach_en.md
new file mode 100644
index 00000000000000..4f83dba218b828
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetuned_squad_badokorach_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_badokorach BertForQuestionAnswering from badokorach
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_badokorach
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_badokorach` is a English model originally trained by badokorach.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_badokorach_en_5.2.0_3.0_1700199417338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_badokorach_en_5.2.0_3.0_1700199417338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_badokorach","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetuned_squad_badokorach", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_badokorach|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/badokorach/bert-base-uncased-finetuned-squad
\ No newline at end of file

From b5039441843511dd0c93f41cff5178b34c1bdc7a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:38:12 +0700
Subject: [PATCH 371/408] Add model
 2023-11-17-finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx

---
 ...e_multilingual_cased_kaarelkaarelson_xx.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx.md b/docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx.md
new file mode 100644
index 00000000000000..21d2427adf42ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Multilingual finetuned_bert_base_multilingual_cased_kaarelkaarelson BertForQuestionAnswering from kaarelkaarelson
+author: John Snow Labs
+name: finetuned_bert_base_multilingual_cased_kaarelkaarelson
+date: 2023-11-17
+tags: [bert, xx, open_source, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_base_multilingual_cased_kaarelkaarelson` is a Multilingual model originally trained by kaarelkaarelson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx_5.2.0_3.0_1700199417568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_multilingual_cased_kaarelkaarelson_xx_5.2.0_3.0_1700199417568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("finetuned_bert_base_multilingual_cased_kaarelkaarelson","xx") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("finetuned_bert_base_multilingual_cased_kaarelkaarelson", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bert_base_multilingual_cased_kaarelkaarelson|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/kaarelkaarelson/finetuned-bert-base-multilingual-cased
\ No newline at end of file

From 0631dfeedcd6d36bfbb9638278bf72fabe4d5d11 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:46:58 +0700
Subject: [PATCH 372/408] Add model
 2023-11-17-question_answering_based_on_bert_en

---
 ...-17-question_answering_based_on_bert_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-question_answering_based_on_bert_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-question_answering_based_on_bert_en.md b/docs/_posts/ahmedlone127/2023-11-17-question_answering_based_on_bert_en.md
new file mode 100644
index 00000000000000..aa4d9ddac485c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-question_answering_based_on_bert_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English question_answering_based_on_bert BertForQuestionAnswering from notoookay
+author: John Snow Labs
+name: question_answering_based_on_bert
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_based_on_bert` is a English model originally trained by notoookay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_based_on_bert_en_5.2.0_3.0_1700200011423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_based_on_bert_en_5.2.0_3.0_1700200011423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("question_answering_based_on_bert","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("question_answering_based_on_bert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_based_on_bert|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/notoookay/question-answering-based-on-bert
\ No newline at end of file

From 7b797e641614fe37bcce2c7cbff3e9cbec1e9365 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:50:07 +0700
Subject: [PATCH 373/408] Add model 2023-11-17-bert_finetuned_squad_wrobinw_en

---
 ...3-11-17-bert_finetuned_squad_wrobinw_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_wrobinw_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_wrobinw_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_wrobinw_en.md
new file mode 100644
index 00000000000000..4f46060988c34c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_wrobinw_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_wrobinw BertForQuestionAnswering from WRobinW
+author: John Snow Labs
+name: bert_finetuned_squad_wrobinw
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_wrobinw` is a English model originally trained by WRobinW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_wrobinw_en_5.2.0_3.0_1700200195204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_wrobinw_en_5.2.0_3.0_1700200195204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_wrobinw","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_wrobinw", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_wrobinw|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/WRobinW/bert-finetuned-squad
\ No newline at end of file

From c7817c496996fe62222ece364734ced4716ed80b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:51:07 +0700
Subject: [PATCH 374/408] Add model
 2023-11-17-bert_finetuned_squad_iamannika_en

---
 ...11-17-bert_finetuned_squad_iamannika_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_iamannika_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_iamannika_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_iamannika_en.md
new file mode 100644
index 00000000000000..8f1ba7594afaeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_iamannika_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_iamannika BertForQuestionAnswering from iamannika
+author: John Snow Labs
+name: bert_finetuned_squad_iamannika
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_iamannika` is a English model originally trained by iamannika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_iamannika_en_5.2.0_3.0_1700200195583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_iamannika_en_5.2.0_3.0_1700200195583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_iamannika","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_iamannika", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_iamannika|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/iamannika/bert-finetuned-squad
\ No newline at end of file

From f0bd978d5d701e515d19e92f8b7d5c998ce34fbc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 12:59:51 +0700
Subject: [PATCH 375/408] Add model 2023-11-17-hw1_span_selection_en

---
 .../2023-11-17-hw1_span_selection_en.md       | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-hw1_span_selection_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-hw1_span_selection_en.md b/docs/_posts/ahmedlone127/2023-11-17-hw1_span_selection_en.md
new file mode 100644
index 00000000000000..9ff843e3c2fca8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-hw1_span_selection_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English hw1_span_selection BertForQuestionAnswering from kyle0518
+author: John Snow Labs
+name: hw1_span_selection
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_span_selection` is a English model originally trained by kyle0518.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_span_selection_en_5.2.0_3.0_1700200784771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_span_selection_en_5.2.0_3.0_1700200784771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hw1_span_selection","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hw1_span_selection", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw1_span_selection|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/kyle0518/HW1_span_selection
\ No newline at end of file

From 39dfcb39bc3bee912b76150e8a114ffaaaf851a3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:02:53 +0700
Subject: [PATCH 376/408] Add model 2023-11-17-hw1_part2_ver27_en

---
 .../2023-11-17-hw1_part2_ver27_en.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver27_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver27_en.md b/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver27_en.md
new file mode 100644
index 00000000000000..35e6dbeb7df133
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver27_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English hw1_part2_ver27 BertForQuestionAnswering from weiiiii0622
+author: John Snow Labs
+name: hw1_part2_ver27
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_part2_ver27` is a English model originally trained by weiiiii0622.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_part2_ver27_en_5.2.0_3.0_1700200967071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_part2_ver27_en_5.2.0_3.0_1700200967071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hw1_part2_ver27","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hw1_part2_ver27", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw1_part2_ver27|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/weiiiii0622/HW1_Part2_ver27
\ No newline at end of file

From fcb1af70a4fae2d11030257fcdb4307966d53fce Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:15:10 +0700
Subject: [PATCH 377/408] Add model 2023-11-17-bert_finetuned_squad_leinadh_en

---
 ...3-11-17-bert_finetuned_squad_leinadh_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_leinadh_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_leinadh_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_leinadh_en.md
new file mode 100644
index 00000000000000..38a0894c1a0878
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_leinadh_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_leinadh BertForQuestionAnswering from Leinadh
+author: John Snow Labs
+name: bert_finetuned_squad_leinadh
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_leinadh` is a English model originally trained by Leinadh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_leinadh_en_5.2.0_3.0_1700201639839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_leinadh_en_5.2.0_3.0_1700201639839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_leinadh","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_leinadh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_leinadh|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Leinadh/bert-finetuned-squad
\ No newline at end of file

From bb9b2674c28ecac92a8f31338228b887844399b5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:17:10 +0700
Subject: [PATCH 378/408] Add model
 2023-11-17-bert_finetuned_squad_gallyamovi_en

---
 ...1-17-bert_finetuned_squad_gallyamovi_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_gallyamovi_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_gallyamovi_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_gallyamovi_en.md
new file mode 100644
index 00000000000000..409723ffe38082
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_gallyamovi_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_gallyamovi BertForQuestionAnswering from gallyamovi
+author: John Snow Labs
+name: bert_finetuned_squad_gallyamovi
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_gallyamovi` is a English model originally trained by gallyamovi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_gallyamovi_en_5.2.0_3.0_1700201822787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_gallyamovi_en_5.2.0_3.0_1700201822787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_gallyamovi","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_gallyamovi", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_gallyamovi|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/gallyamovi/bert-finetuned-squad
\ No newline at end of file

From 0cd02f8412fd0ec453132bbfa1ce80e524203ec3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:20:13 +0700
Subject: [PATCH 379/408] Add model 2023-11-17-adl2023_hw1_span_selection_en

---
 ...023-11-17-adl2023_hw1_span_selection_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-adl2023_hw1_span_selection_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-adl2023_hw1_span_selection_en.md b/docs/_posts/ahmedlone127/2023-11-17-adl2023_hw1_span_selection_en.md
new file mode 100644
index 00000000000000..3df7e16584d47b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-adl2023_hw1_span_selection_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English adl2023_hw1_span_selection BertForQuestionAnswering from dean22029
+author: John Snow Labs
+name: adl2023_hw1_span_selection
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adl2023_hw1_span_selection` is a English model originally trained by dean22029.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adl2023_hw1_span_selection_en_5.2.0_3.0_1700201995540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adl2023_hw1_span_selection_en_5.2.0_3.0_1700201995540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("adl2023_hw1_span_selection","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("adl2023_hw1_span_selection", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adl2023_hw1_span_selection|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dean22029/adl2023_hw1_span_selection
\ No newline at end of file

From 626eb8c0c44b2038857f175c75c6089e41ff1371 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:25:13 +0700
Subject: [PATCH 380/408] Add model 2023-11-17-bert_finetuned_squad_jmoraes_en

---
 ...3-11-17-bert_finetuned_squad_jmoraes_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jmoraes_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jmoraes_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jmoraes_en.md
new file mode 100644
index 00000000000000..bdff33164ccbe5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jmoraes_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_jmoraes BertForQuestionAnswering from jmoraes
+author: John Snow Labs
+name: bert_finetuned_squad_jmoraes
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jmoraes` is a English model originally trained by jmoraes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jmoraes_en_5.2.0_3.0_1700202304817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jmoraes_en_5.2.0_3.0_1700202304817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jmoraes","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_jmoraes", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jmoraes|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/jmoraes/bert-finetuned-squad
\ No newline at end of file

From afc3ca631ca0793ba288c21dabed39e5ba3fbe5f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:37:14 +0700
Subject: [PATCH 381/408] Add model
 2023-11-17-bert_finetuned_squad_ashutosh2109_en

---
 ...17-bert_finetuned_squad_ashutosh2109_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ashutosh2109_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ashutosh2109_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ashutosh2109_en.md
new file mode 100644
index 00000000000000..b103df6f8e8b0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_ashutosh2109_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_ashutosh2109 BertForQuestionAnswering from ashutosh2109
+author: John Snow Labs
+name: bert_finetuned_squad_ashutosh2109
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ashutosh2109` is a English model originally trained by ashutosh2109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ashutosh2109_en_5.2.0_3.0_1700203021936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ashutosh2109_en_5.2.0_3.0_1700203021936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ashutosh2109","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_ashutosh2109", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ashutosh2109|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ashutosh2109/bert-finetuned-squad
\ No newline at end of file

From 0786323942114920405743002c9aa28743cb9b2f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:38:13 +0700
Subject: [PATCH 382/408] Add model
 2023-11-17-autotrain_robertaqanda_99403147318_en

---
 ...7-autotrain_robertaqanda_99403147318_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-autotrain_robertaqanda_99403147318_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-autotrain_robertaqanda_99403147318_en.md b/docs/_posts/ahmedlone127/2023-11-17-autotrain_robertaqanda_99403147318_en.md
new file mode 100644
index 00000000000000..e785947bb65d24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-autotrain_robertaqanda_99403147318_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English autotrain_robertaqanda_99403147318 BertForQuestionAnswering from Samis922
+author: John Snow Labs
+name: autotrain_robertaqanda_99403147318
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_robertaqanda_99403147318` is a English model originally trained by Samis922.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_robertaqanda_99403147318_en_5.2.0_3.0_1700203027511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_robertaqanda_99403147318_en_5.2.0_3.0_1700203027511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("autotrain_robertaqanda_99403147318","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("autotrain_robertaqanda_99403147318", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_robertaqanda_99403147318|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Samis922/autotrain-robertaqanda-99403147318
\ No newline at end of file

From ec22f06a7f9045863932c00783a20234aaf786aa Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:39:14 +0700
Subject: [PATCH 383/408] Add model
 2023-11-17-bert_finetuned_uncased_squad_v2_en

---
 ...1-17-bert_finetuned_uncased_squad_v2_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_uncased_squad_v2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_uncased_squad_v2_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_uncased_squad_v2_en.md
new file mode 100644
index 00000000000000..50871fca17c5eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_uncased_squad_v2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_uncased_squad_v2 BertForQuestionAnswering from aai520-group6
+author: John Snow Labs
+name: bert_finetuned_uncased_squad_v2
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_uncased_squad_v2` is a English model originally trained by aai520-group6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_uncased_squad_v2_en_5.2.0_3.0_1700203141990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_uncased_squad_v2_en_5.2.0_3.0_1700203141990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_uncased_squad_v2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_uncased_squad_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_uncased_squad_v2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/aai520-group6/bert-finetuned-uncased-squad_v2
\ No newline at end of file

From 935720f2460c1b7da7f1b36f881941aa6cefbd4c Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:40:14 +0700
Subject: [PATCH 384/408] Add model
 2023-11-17-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en

---
 ..._southern_sotho_false_fh_true_hs_666_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..5f7c0544bd8f82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en_5.2.0_3.0_1700203135082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666_en_5.2.0_3.0_1700203135082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_9119_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-06-wd-0.001-dp-0.2-ss-9119-st-False-fh-True-hs-666
\ No newline at end of file

From 8d5438f0271ddddf57cc3047553bcb03d910cfb3 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:41:14 +0700
Subject: [PATCH 385/408] Add model 2023-11-17-close_book_2_en

---
 .../2023-11-17-close_book_2_en.md             | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-close_book_2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-close_book_2_en.md b/docs/_posts/ahmedlone127/2023-11-17-close_book_2_en.md
new file mode 100644
index 00000000000000..86985549e407b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-close_book_2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English close_book_2 BertForQuestionAnswering from Ahmed007
+author: John Snow Labs
+name: close_book_2
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`close_book_2` is a English model originally trained by Ahmed007.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/close_book_2_en_5.2.0_3.0_1700203204243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/close_book_2_en_5.2.0_3.0_1700203204243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("close_book_2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("close_book_2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|close_book_2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Ahmed007/Close_book_2
\ No newline at end of file

From e98b47cfabf75e335b31102c98c20b67242fc7ab Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:57:19 +0700
Subject: [PATCH 386/408] Add model
 2023-11-17-bert_base_chinese_finetuned_qa_b8_10_en

---
 ...bert_base_chinese_finetuned_qa_b8_10_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_10_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_10_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_10_en.md
new file mode 100644
index 00000000000000..a825a5e290b62f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_chinese_finetuned_qa_b8_10_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_chinese_finetuned_qa_b8_10 BertForQuestionAnswering from sharkMeow
+author: John Snow Labs
+name: bert_base_chinese_finetuned_qa_b8_10
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_qa_b8_10` is a English model originally trained by sharkMeow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_qa_b8_10_en_5.2.0_3.0_1700204233166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_qa_b8_10_en_5.2.0_3.0_1700204233166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_chinese_finetuned_qa_b8_10","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_chinese_finetuned_qa_b8_10", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_chinese_finetuned_qa_b8_10|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/sharkMeow/bert-base-chinese-finetuned-QA-b8-10
\ No newline at end of file

From 3ae8a1029760b272bba3dc955f52e7a60732bd19 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 13:59:46 +0700
Subject: [PATCH 387/408] Add model 2023-11-17-bert_finetuned_squad_jchhabra_en

---
 ...-11-17-bert_finetuned_squad_jchhabra_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jchhabra_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jchhabra_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jchhabra_en.md
new file mode 100644
index 00000000000000..31e96e7c42d3c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_jchhabra_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_jchhabra BertForQuestionAnswering from jchhabra
+author: John Snow Labs
+name: bert_finetuned_squad_jchhabra
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jchhabra` is a English model originally trained by jchhabra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jchhabra_en_5.2.0_3.0_1700204370272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jchhabra_en_5.2.0_3.0_1700204370272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jchhabra","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_jchhabra", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jchhabra|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/jchhabra/bert-finetuned-squad
\ No newline at end of file

From 7e75c7ba95c92dbb3a99dddfb3d81a3c42e317a5 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:00:46 +0700
Subject: [PATCH 388/408] Add model
 2023-11-17-bert_finetuned_squad_kellyxuanlin_en

---
 ...17-bert_finetuned_squad_kellyxuanlin_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_kellyxuanlin_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_kellyxuanlin_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_kellyxuanlin_en.md
new file mode 100644
index 00000000000000..18bad0216d36a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_kellyxuanlin_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_kellyxuanlin BertForQuestionAnswering from kellyxuanlin
+author: John Snow Labs
+name: bert_finetuned_squad_kellyxuanlin
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_kellyxuanlin` is a English model originally trained by kellyxuanlin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_kellyxuanlin_en_5.2.0_3.0_1700204374413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_kellyxuanlin_en_5.2.0_3.0_1700204374413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_kellyxuanlin","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_kellyxuanlin", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_kellyxuanlin|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/kellyxuanlin/bert-finetuned-squad
\ No newline at end of file

From a217ed050c76daca4b9e0e630c4252745c85f8f7 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:01:47 +0700
Subject: [PATCH 389/408] Add model 2023-11-17-hw1_part2_ver26_en

---
 .../2023-11-17-hw1_part2_ver26_en.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver26_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver26_en.md b/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver26_en.md
new file mode 100644
index 00000000000000..33f443df6df2dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver26_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English hw1_part2_ver26 BertForQuestionAnswering from weiiiii0622
+author: John Snow Labs
+name: hw1_part2_ver26
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_part2_ver26` is a English model originally trained by weiiiii0622.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_part2_ver26_en_5.2.0_3.0_1700204457155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_part2_ver26_en_5.2.0_3.0_1700204457155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hw1_part2_ver26","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hw1_part2_ver26", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw1_part2_ver26|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/weiiiii0622/HW1_Part2_ver26
\ No newline at end of file

From f60868d4f430d467437cff46b7a9a9b4b1886d76 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:02:47 +0700
Subject: [PATCH 390/408] Add model 2023-11-17-pubmed_bert_squad_covidqa_en

---
 ...2023-11-17-pubmed_bert_squad_covidqa_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-pubmed_bert_squad_covidqa_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-pubmed_bert_squad_covidqa_en.md b/docs/_posts/ahmedlone127/2023-11-17-pubmed_bert_squad_covidqa_en.md
new file mode 100644
index 00000000000000..1c9304db414f12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-pubmed_bert_squad_covidqa_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English pubmed_bert_squad_covidqa BertForQuestionAnswering from Sarmila
+author: John Snow Labs
+name: pubmed_bert_squad_covidqa
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmed_bert_squad_covidqa` is a English model originally trained by Sarmila.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmed_bert_squad_covidqa_en_5.2.0_3.0_1700204374667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmed_bert_squad_covidqa_en_5.2.0_3.0_1700204374667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("pubmed_bert_squad_covidqa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("pubmed_bert_squad_covidqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubmed_bert_squad_covidqa|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/Sarmila/pubmed-bert-squad-covidqa
\ No newline at end of file

From 795a592a4699f2ddd5fef00b878bee5bcf221d4f Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:17:59 +0700
Subject: [PATCH 391/408] Add model
 2023-11-17-ntu_adl_span_selection_cluecorpussmall_en

---
 ...u_adl_span_selection_cluecorpussmall_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-ntu_adl_span_selection_cluecorpussmall_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-ntu_adl_span_selection_cluecorpussmall_en.md b/docs/_posts/ahmedlone127/2023-11-17-ntu_adl_span_selection_cluecorpussmall_en.md
new file mode 100644
index 00000000000000..46c37305aa0fe7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-ntu_adl_span_selection_cluecorpussmall_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English ntu_adl_span_selection_cluecorpussmall BertForQuestionAnswering from xjlulu
+author: John Snow Labs
+name: ntu_adl_span_selection_cluecorpussmall
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ntu_adl_span_selection_cluecorpussmall` is a English model originally trained by xjlulu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_cluecorpussmall_en_5.2.0_3.0_1700205472025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ntu_adl_span_selection_cluecorpussmall_en_5.2.0_3.0_1700205472025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ntu_adl_span_selection_cluecorpussmall","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("ntu_adl_span_selection_cluecorpussmall", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ntu_adl_span_selection_cluecorpussmall|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.1 MB|
+
+## References
+
+https://huggingface.co/xjlulu/ntu_adl_span_selection_cluecorpussmall
\ No newline at end of file

From d3951a4aa685fbc549458b4be2aa184b62754dcb Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:20:36 +0700
Subject: [PATCH 392/408] Add model
 2023-11-17-bert_finetuned_squad_golightly_en

---
 ...11-17-bert_finetuned_squad_golightly_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_golightly_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_golightly_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_golightly_en.md
new file mode 100644
index 00000000000000..6f168c8a5d559e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_golightly_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_golightly BertForQuestionAnswering from golightly
+author: John Snow Labs
+name: bert_finetuned_squad_golightly
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_golightly` is a English model originally trained by golightly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_golightly_en_5.2.0_3.0_1700205623429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_golightly_en_5.2.0_3.0_1700205623429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_golightly","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_golightly", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_golightly|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/golightly/bert-finetuned-squad
\ No newline at end of file

From e6326cdfaaaa27b5957acbc01635566ee6448fdc Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:21:36 +0700
Subject: [PATCH 393/408] Add model
 2023-11-17-bert_finetuned_squad_strongwar_en

---
 ...11-17-bert_finetuned_squad_strongwar_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_strongwar_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_strongwar_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_strongwar_en.md
new file mode 100644
index 00000000000000..a794694264f4b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_strongwar_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_strongwar BertForQuestionAnswering from strongwar
+author: John Snow Labs
+name: bert_finetuned_squad_strongwar
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_strongwar` is a English model originally trained by strongwar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_strongwar_en_5.2.0_3.0_1700205623457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_strongwar_en_5.2.0_3.0_1700205623457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_strongwar","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_strongwar", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_strongwar|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/strongwar/bert-finetuned-squad
\ No newline at end of file

From 043841e9eed6e77e26a91b5580723d81af7d3ca2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:22:36 +0700
Subject: [PATCH 394/408] Add model 2023-11-17-sports_klue_finetuned_korquad_en

---
 ...-11-17-sports_klue_finetuned_korquad_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-sports_klue_finetuned_korquad_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-sports_klue_finetuned_korquad_en.md b/docs/_posts/ahmedlone127/2023-11-17-sports_klue_finetuned_korquad_en.md
new file mode 100644
index 00000000000000..8ffc1cedfeea06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-sports_klue_finetuned_korquad_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English sports_klue_finetuned_korquad BertForQuestionAnswering from Kdogs
+author: John Snow Labs
+name: sports_klue_finetuned_korquad
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sports_klue_finetuned_korquad` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_en_5.2.0_3.0_1700205629288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_en_5.2.0_3.0_1700205629288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("sports_klue_finetuned_korquad","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("sports_klue_finetuned_korquad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sports_klue_finetuned_korquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/Kdogs/sports_klue_finetuned_korquad
\ No newline at end of file

From e5c048c4546b12bd90dd2e20270b926c3dd49697 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:23:36 +0700
Subject: [PATCH 395/408] Add model
 2023-11-17-klue_bert_base_finetuned_squad_kor_v1_ko

---
 ...lue_bert_base_finetuned_squad_kor_v1_ko.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-klue_bert_base_finetuned_squad_kor_v1_ko.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-klue_bert_base_finetuned_squad_kor_v1_ko.md b/docs/_posts/ahmedlone127/2023-11-17-klue_bert_base_finetuned_squad_kor_v1_ko.md
new file mode 100644
index 00000000000000..0d038c76d01000
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-klue_bert_base_finetuned_squad_kor_v1_ko.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: Korean klue_bert_base_finetuned_squad_kor_v1 BertForQuestionAnswering from yjgwak
+author: John Snow Labs
+name: klue_bert_base_finetuned_squad_kor_v1
+date: 2023-11-17
+tags: [bert, ko, open_source, question_answering, onnx]
+task: Question Answering
+language: ko
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`klue_bert_base_finetuned_squad_kor_v1` is a Korean model originally trained by yjgwak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/klue_bert_base_finetuned_squad_kor_v1_ko_5.2.0_3.0_1700205694463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/klue_bert_base_finetuned_squad_kor_v1_ko_5.2.0_3.0_1700205694463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("klue_bert_base_finetuned_squad_kor_v1","ko") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("klue_bert_base_finetuned_squad_kor_v1", "ko")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|klue_bert_base_finetuned_squad_kor_v1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ko|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/yjgwak/klue-bert-base-finetuned-squad-kor-v1
\ No newline at end of file

From cc7cedbeea2cfda0293bd8397c1967ae0e4d63d8 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:42:36 +0700
Subject: [PATCH 396/408] Add model
 2023-11-17-bert_finetuned_squad_legalbert_en

---
 ...11-17-bert_finetuned_squad_legalbert_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_legalbert_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_legalbert_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_legalbert_en.md
new file mode 100644
index 00000000000000..4383799f2ed5bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_legalbert_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_legalbert BertForQuestionAnswering from Jasu
+author: John Snow Labs
+name: bert_finetuned_squad_legalbert
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_legalbert` is a English model originally trained by Jasu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_legalbert_en_5.2.0_3.0_1700206944958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_legalbert_en_5.2.0_3.0_1700206944958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_legalbert","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_legalbert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_legalbert|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/Jasu/bert-finetuned-squad-legalbert
\ No newline at end of file

From 7b4cc764385c64f787e3df709b2fa313b27d3ca6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:43:36 +0700
Subject: [PATCH 397/408] Add model
 2023-11-17-bert_finetuned_squad_mongdiutindei_en

---
 ...7-bert_finetuned_squad_mongdiutindei_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_mongdiutindei_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_mongdiutindei_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_mongdiutindei_en.md
new file mode 100644
index 00000000000000..21283627b6aa1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_mongdiutindei_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_mongdiutindei BertForQuestionAnswering from mongdiutindei
+author: John Snow Labs
+name: bert_finetuned_squad_mongdiutindei
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_mongdiutindei` is a English model originally trained by mongdiutindei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_mongdiutindei_en_5.2.0_3.0_1700206946653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_mongdiutindei_en_5.2.0_3.0_1700206946653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_mongdiutindei","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_mongdiutindei", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_mongdiutindei|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|400.6 MB|
+
+## References
+
+https://huggingface.co/mongdiutindei/bert-finetuned-squad
\ No newline at end of file

From b20f709ca178d852aef17d9b826666b980fd4d9b Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:46:27 +0700
Subject: [PATCH 398/408] Add model 2023-11-17-finetuned_bert_base_arabertv2_en

---
 ...-11-17-finetuned_bert_base_arabertv2_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_arabertv2_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_arabertv2_en.md b/docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_arabertv2_en.md
new file mode 100644
index 00000000000000..4b360350a16bf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-finetuned_bert_base_arabertv2_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English finetuned_bert_base_arabertv2 BertForQuestionAnswering from kaarelkaarelson
+author: John Snow Labs
+name: finetuned_bert_base_arabertv2
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_base_arabertv2` is a English model originally trained by kaarelkaarelson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_arabertv2_en_5.2.0_3.0_1700207170853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_arabertv2_en_5.2.0_3.0_1700207170853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("finetuned_bert_base_arabertv2","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("finetuned_bert_base_arabertv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bert_base_arabertv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|504.8 MB|
+
+## References
+
+https://huggingface.co/kaarelkaarelson/finetuned-bert-base-arabertv2
\ No newline at end of file

From 777693258c16889bcde7960b12df6bf42efec0c6 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 14:47:27 +0700
Subject: [PATCH 399/408] Add model 2023-11-17-spec_seq_lab_bengali_en

---
 .../2023-11-17-spec_seq_lab_bengali_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-spec_seq_lab_bengali_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-spec_seq_lab_bengali_en.md b/docs/_posts/ahmedlone127/2023-11-17-spec_seq_lab_bengali_en.md
new file mode 100644
index 00000000000000..4dcda727736813
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-spec_seq_lab_bengali_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English spec_seq_lab_bengali BertForQuestionAnswering from mathildeparlo
+author: John Snow Labs
+name: spec_seq_lab_bengali
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spec_seq_lab_bengali` is a English model originally trained by mathildeparlo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spec_seq_lab_bengali_en_5.2.0_3.0_1700207170871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spec_seq_lab_bengali_en_5.2.0_3.0_1700207170871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("spec_seq_lab_bengali","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("spec_seq_lab_bengali", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spec_seq_lab_bengali|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/mathildeparlo/spec_seq_lab_bengali
\ No newline at end of file

From 02a8777c0addc8ad32f18ec776f8189c733c8066 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:09:36 +0700
Subject: [PATCH 400/408] Add model
 2023-11-17-bert_base_uncased_coqa_willheld_en

---
 ...1-17-bert_base_uncased_coqa_willheld_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_coqa_willheld_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_coqa_willheld_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_coqa_willheld_en.md
new file mode 100644
index 00000000000000..91a2f309ca68bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_base_uncased_coqa_willheld_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_base_uncased_coqa_willheld BertForQuestionAnswering from WillHeld
+author: John Snow Labs
+name: bert_base_uncased_coqa_willheld
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_coqa_willheld` is a English model originally trained by WillHeld.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_coqa_willheld_en_5.2.0_3.0_1700208569250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_coqa_willheld_en_5.2.0_3.0_1700208569250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_coqa_willheld","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_base_uncased_coqa_willheld", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_coqa_willheld|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/WillHeld/bert-base-uncased-coqa
\ No newline at end of file

From 0a39a4cf0b433f8f8b99688038b0169bf3457b9d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:13:38 +0700
Subject: [PATCH 401/408] Add model 2023-11-17-bert_30_en

---
 .../ahmedlone127/2023-11-17-bert_30_en.md     | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_30_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_30_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_30_en.md
new file mode 100644
index 00000000000000..b6b42e493c61ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_30_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_30 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_30
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_30` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_30_en_5.2.0_3.0_1700208805027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_30_en_5.2.0_3.0_1700208805027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_30","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_30", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_30|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-30
\ No newline at end of file

From ec695c8759e1cc95f0e00f0ba8af009fba5fbd59 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:14:38 +0700
Subject: [PATCH 402/408] Add model 2023-11-17-bert_covid_21_en

---
 .../2023-11-17-bert_covid_21_en.md            | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_covid_21_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_covid_21_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_covid_21_en.md
new file mode 100644
index 00000000000000..b7031b7ec64f88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_covid_21_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_covid_21 BertForQuestionAnswering from hung200504
+author: John Snow Labs
+name: bert_covid_21
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_covid_21` is a English model originally trained by hung200504.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_covid_21_en_5.2.0_3.0_1700208806304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_covid_21_en_5.2.0_3.0_1700208806304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_covid_21","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_covid_21", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_covid_21|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/hung200504/bert-covid-21
\ No newline at end of file

From 75e7519c9d261ed311aaa5a6b8f2c01adbea7649 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:18:12 +0700
Subject: [PATCH 403/408] Add model
 2023-11-17-bert_finetuned_squad_alexperkin_en

---
 ...1-17-bert_finetuned_squad_alexperkin_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_alexperkin_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_alexperkin_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_alexperkin_en.md
new file mode 100644
index 00000000000000..c991dbfeb02aff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_alexperkin_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_alexperkin BertForQuestionAnswering from AlexPerkin
+author: John Snow Labs
+name: bert_finetuned_squad_alexperkin
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_alexperkin` is a English model originally trained by AlexPerkin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alexperkin_en_5.2.0_3.0_1700209084264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alexperkin_en_5.2.0_3.0_1700209084264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_alexperkin","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_alexperkin", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_alexperkin|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/AlexPerkin/bert-finetuned-squad
\ No newline at end of file

From 2ef28c30427ea68c1065b812f65fa75e4bbace6d Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:31:23 +0700
Subject: [PATCH 404/408] Add model 2023-11-17-bioformer_8l_squad1_en

---
 .../2023-11-17-bioformer_8l_squad1_en.md      | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bioformer_8l_squad1_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bioformer_8l_squad1_en.md b/docs/_posts/ahmedlone127/2023-11-17-bioformer_8l_squad1_en.md
new file mode 100644
index 00000000000000..861174300d0b6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bioformer_8l_squad1_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bioformer_8l_squad1 BertForQuestionAnswering from bioformers
+author: John Snow Labs
+name: bioformer_8l_squad1
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bioformer_8l_squad1` is a English model originally trained by bioformers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bioformer_8l_squad1_en_5.2.0_3.0_1700209877808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bioformer_8l_squad1_en_5.2.0_3.0_1700209877808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bioformer_8l_squad1","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bioformer_8l_squad1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bioformer_8l_squad1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|158.5 MB|
+
+## References
+
+https://huggingface.co/bioformers/bioformer-8L-squad1
\ No newline at end of file

From b39b475f505d65d86d9eb836ad7766323181140a Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:32:23 +0700
Subject: [PATCH 405/408] Add model
 2023-11-17-bert_finetuned_squad_raychang7_en

---
 ...11-17-bert_finetuned_squad_raychang7_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_raychang7_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_raychang7_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_raychang7_en.md
new file mode 100644
index 00000000000000..d521cd8723e542
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_raychang7_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_raychang7 BertForQuestionAnswering from raychang7
+author: John Snow Labs
+name: bert_finetuned_squad_raychang7
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_raychang7` is a English model originally trained by raychang7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_raychang7_en_5.2.0_3.0_1700209877967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_raychang7_en_5.2.0_3.0_1700209877967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_raychang7","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_raychang7", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_raychang7|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/raychang7/bert-finetuned-squad
\ No newline at end of file

From 745cb1f2cd34b762e1cb8392b54350a680f34581 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:35:41 +0700
Subject: [PATCH 406/408] Add model 2023-11-17-hotel_qa_model_en

---
 .../2023-11-17-hotel_qa_model_en.md           | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-hotel_qa_model_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-hotel_qa_model_en.md b/docs/_posts/ahmedlone127/2023-11-17-hotel_qa_model_en.md
new file mode 100644
index 00000000000000..8ce8cb243f0ac2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-hotel_qa_model_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English hotel_qa_model BertForQuestionAnswering from nova-sqoin
+author: John Snow Labs
+name: hotel_qa_model
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hotel_qa_model` is a English model originally trained by nova-sqoin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hotel_qa_model_en_5.2.0_3.0_1700210132942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hotel_qa_model_en_5.2.0_3.0_1700210132942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hotel_qa_model","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hotel_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hotel_qa_model|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|405.0 MB|
+
+## References
+
+https://huggingface.co/nova-sqoin/hotel_qa_model
\ No newline at end of file

From 75b2f0dd755e537030c4b9f9b9633be74d25ddc9 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:40:38 +0700
Subject: [PATCH 407/408] Add model 2023-11-17-hw1_part2_ver12_en

---
 .../2023-11-17-hw1_part2_ver12_en.md          | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver12_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver12_en.md b/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver12_en.md
new file mode 100644
index 00000000000000..b2e463dc4a8922
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-hw1_part2_ver12_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English hw1_part2_ver12 BertForQuestionAnswering from weiiiii0622
+author: John Snow Labs
+name: hw1_part2_ver12
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_part2_ver12` is a English model originally trained by weiiiii0622.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_part2_ver12_en_5.2.0_3.0_1700210427798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_part2_ver12_en_5.2.0_3.0_1700210427798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("hw1_part2_ver12","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("hw1_part2_ver12", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw1_part2_ver12|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/weiiiii0622/HW1_Part2_ver12
\ No newline at end of file

From 28e0697457d7e7d41b28195719e57d0e5672aee2 Mon Sep 17 00:00:00 2001
From: ahmedlone127 <ahmedlone127@gmail.com>
Date: Fri, 17 Nov 2023 15:41:39 +0700
Subject: [PATCH 408/408] Add model
 2023-11-17-bert_finetuned_squad_v1_sooolee_en

---
 ...1-17-bert_finetuned_squad_v1_sooolee_en.md | 93 +++++++++++++++++++
 1 file changed, 93 insertions(+)
 create mode 100644 docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_v1_sooolee_en.md

diff --git a/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_v1_sooolee_en.md b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_v1_sooolee_en.md
new file mode 100644
index 00000000000000..388ddff7022492
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2023-11-17-bert_finetuned_squad_v1_sooolee_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: English bert_finetuned_squad_v1_sooolee BertForQuestionAnswering from sooolee
+author: John Snow Labs
+name: bert_finetuned_squad_v1_sooolee
+date: 2023-11-17
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_v1_sooolee` is a English model originally trained by sooolee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_v1_sooolee_en_5.2.0_3.0_1700210428957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_v1_sooolee_en_5.2.0_3.0_1700210428957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_v1_sooolee","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("bert_finetuned_squad_v1_sooolee", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_v1_sooolee|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/sooolee/bert-finetuned-squad-v1
\ No newline at end of file