diff --git a/docs/_posts/ahmedlone127/2024-07-01-mpnet_base_token_classifier_en.md b/docs/_posts/ahmedlone127/2024-07-01-mpnet_base_token_classifier_en.md
new file mode 100644
index 00000000000000..b8bee8923f97bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-07-01-mpnet_base_token_classifier_en.md
@@ -0,0 +1,91 @@
+---
+layout: model
+title: MPnetForTokenClassification Base Model English
+author: John Snow Labs
+name: mpnet_base_token_classifier
+date: 2024-07-01
+tags: [token_classification, mpnet, ner, en, open_source, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.4.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForTokenClassification, fine tuned in huggingface in house and then imported to Spark-NLP o provide scalability and production-readiness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_token_classifier_en_5.4.0_3.0_1719843589238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_token_classifier_en_5.4.0_3.0_1719843589238.zip){:.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 = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = MPNetForTokenClassification.pretrained("mpnet_base_token_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = MPNetForTokenClassification.pretrained("mpnet_base_token_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_token_classifier|
+|Compatibility:|Spark NLP 5.4.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[token, document]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|395.9 MB|
+|Case sensitive:|true|
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-07-03-mistral_7b_en.md b/docs/_posts/ahmedlone127/2024-07-03-mistral_7b_en.md
new file mode 100644
index 00000000000000..e6ce7cf9ed4cfc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-07-03-mistral_7b_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Mistral text-to-text model 7b int8
+author: John Snow Labs
+name: mistral_7b
+date: 2024-07-03
+tags: [mistral, en, llm, open_source, openvino]
+task: Text Generation
+language: en
+edition: Spark NLP 5.4.0
+spark_version: 3.0
+supported: true
+engine: openvino
+annotator: MistralTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MistralTransformer, adapted and imported into Spark NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mistral_7b_en_5.4.0_3.0_1720021606199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mistral_7b_en_5.4.0_3.0_1720021606199.zip){:.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 = DocumentAssembler() \
+	.setInputCol('text') \
+	.setOutputCol('document')
+
+mistral = MistralTransformer .pretrained() \
+	.setMaxOutputLength(50) \
+	.setDoSample(False) \
+	.setInputCols(["document"]) \
+	.setOutputCol("mistral_generation")
+
+pipeline = Pipeline().setStages([documentAssembler, mistral])
+data = spark.createDataFrame([["Who is the founder of Spark-NLP?"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+	.setInputCols("text")
+	.setOutputCols("document")
+
+val mistral = MistralTransformer .pretrained()
+	.setMaxOutputLength(50)
+	.setDoSample(False)
+	.setInputCols(["document"])
+	.setOutputCol("mistral_generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, mistral))
+val data = Seq("Who is the founder of Spark-NLP?").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mistral_7b|
+|Compatibility:|Spark NLP 5.4.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|6.6 GB|