Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

2024-01-01-bge_small_en #14116

Merged
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
85 changes: 85 additions & 0 deletions docs/_posts/maziyarpanahi/2024-01-01-bge_base_en.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,85 @@
---
layout: model
title: BAAI general embedding English (bge_base)
author: John Snow Labs
name: bge_base
date: 2024-01-01
tags: [bert, bge, onnx, en, open_source]
task: Embeddings
language: en
edition: Spark NLP 5.2.1
spark_version: 3.0
supported: true
engine: onnx
annotator: BGEEmbeddings
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search.
And it also can be used in vector database for LLMs.

`bge` is short for `BAAI general embedding`.

| Model | Language | Description | query instruction for retrieval\* |
|:-------------------------------|:--------:| :--------:| :--------:|
| [BAAI/bge-large-en](https://huggingface.co/BAAI/bge-large-en) | English | rank **1st** in [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en) | English | rank **2nd** in [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-small-en](https://huggingface.co/BAAI/bge-small-en) | English | a small-scale model but with competitive performance | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-large-zh](https://huggingface.co/BAAI/bge-large-zh) | Chinese | rank **1st** in [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB) benchmark | `为这个句子生成表示以用于检索相关文章:` |
| [BAAI/bge-large-zh-noinstruct](https://huggingface.co/BAAI/bge-large-zh-noinstruct) | Chinese | This model is trained without instruction, and rank **2nd** in [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB) benchmark | |
| [BAAI/bge-base-zh](https://huggingface.co/BAAI/bge-base-zh) | Chinese | a base-scale model but has similar ability with `bge-large-zh` | `为这个句子生成表示以用于检索相关文章:` |
| [BAAI/bge-small-zh](https://huggingface.co/BAAI/bge-small-zh) | Chinese | a small-scale model but with competitive performance | `为这个句子生成表示以用于检索相关文章:` |

## 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/bge_base_en_5.2.1_3.0_1704107443716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_en_5.2.1_3.0_1704107443716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

## How to use



<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
document = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")

embeddings = BGEEmbeddings.pretrained("bge_base", "en")\
.setInputCols("document")\
.setOutputCol("embeddings")
```
```scala
val document = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")

val embeddings = BGEEmbeddings.pretrained("bge_base", "en")
.setInputCols("document")
.setOutputCol("embeddings")
```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|bge_base|
|Compatibility:|Spark NLP 5.2.1+|
|License:|Open Source|
|Edition:|Official|
|Input Labels:|[document]|
|Output Labels:|[bge]|
|Language:|en|
|Size:|258.7 MB|
87 changes: 87 additions & 0 deletions docs/_posts/maziyarpanahi/2024-01-01-bge_large_en.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,87 @@
---
layout: model
title: BAAI general embedding English (bge_large)
author: John Snow Labs
name: bge_large
date: 2024-01-01
tags: [en, onnx, bert, bge, open_source]
task: Embeddings
language: en
edition: Spark NLP 5.2.1
spark_version: 3.0
supported: true
engine: onnx
annotator: BGEEmbeddings
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search.
And it also can be used in vector database for LLMs.

`bge` is short for `BAAI general embedding`.

| Model | Language | Description | query instruction for retrieval\* |
|:-------------------------------|:--------:| :--------:| :--------:|
| [BAAI/bge-large-en](https://huggingface.co/BAAI/bge-large-en) | English | rank **1st** in [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en) | English | rank **2nd** in [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-small-en](https://huggingface.co/BAAI/bge-small-en) | English | a small-scale model but with competitive performance | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-large-zh](https://huggingface.co/BAAI/bge-large-zh) | Chinese | rank **1st** in [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB) benchmark | `为这个句子生成表示以用于检索相关文章:` |
| [BAAI/bge-large-zh-noinstruct](https://huggingface.co/BAAI/bge-large-zh-noinstruct) | Chinese | This model is trained without instruction, and rank **2nd** in [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB) benchmark | |
| [BAAI/bge-base-zh](https://huggingface.co/BAAI/bge-base-zh) | Chinese | a base-scale model but has similar ability with `bge-large-zh` | `为这个句子生成表示以用于检索相关文章:` |
| [BAAI/bge-small-zh](https://huggingface.co/BAAI/bge-small-zh) | Chinese | a small-scale model but with competitive performance | `为这个句子生成表示以用于检索相关文章:` |

## 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/bge_large_en_5.2.1_3.0_1704108288598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_en_5.2.1_3.0_1704108288598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

## How to use



<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
document = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")


embeddings = BGEEmbeddings.pretrained("bge_large", "en")\
.setInputCols("document")\
.setOutputCol("embeddings")
```
```scala
val document = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")


val embeddings = BGEEmbeddings.pretrained("bge_large", "en")
.setInputCols("document")
.setOutputCol("embeddings")
```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|bge_large|
|Compatibility:|Spark NLP 5.2.1+|
|License:|Open Source|
|Edition:|Official|
|Input Labels:|[document]|
|Output Labels:|[bge]|
|Language:|en|
|Size:|794.1 MB|
85 changes: 85 additions & 0 deletions docs/_posts/maziyarpanahi/2024-01-01-bge_small_en.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,85 @@
---
layout: model
title: BAAI general embedding English (bge_small)
author: John Snow Labs
name: bge_small
date: 2024-01-01
tags: [onnx, bert, bge, en, open_source]
task: Embeddings
language: en
edition: Spark NLP 5.2.1
spark_version: 3.0
supported: true
engine: onnx
annotator: BGEEmbeddings
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search.
And it also can be used in vector database for LLMs.

`bge` is short for `BAAI general embedding`.

| Model | Language | Description | query instruction for retrieval\* |
|:-------------------------------|:--------:| :--------:| :--------:|
| [BAAI/bge-large-en](https://huggingface.co/BAAI/bge-large-en) | English | rank **1st** in [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en) | English | rank **2nd** in [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-small-en](https://huggingface.co/BAAI/bge-small-en) | English | a small-scale model but with competitive performance | `Represent this sentence for searching relevant passages: ` |
| [BAAI/bge-large-zh](https://huggingface.co/BAAI/bge-large-zh) | Chinese | rank **1st** in [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB) benchmark | `为这个句子生成表示以用于检索相关文章:` |
| [BAAI/bge-large-zh-noinstruct](https://huggingface.co/BAAI/bge-large-zh-noinstruct) | Chinese | This model is trained without instruction, and rank **2nd** in [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB) benchmark | |
| [BAAI/bge-base-zh](https://huggingface.co/BAAI/bge-base-zh) | Chinese | a base-scale model but has similar ability with `bge-large-zh` | `为这个句子生成表示以用于检索相关文章:` |
| [BAAI/bge-small-zh](https://huggingface.co/BAAI/bge-small-zh) | Chinese | a small-scale model but with competitive performance | `为这个句子生成表示以用于检索相关文章:` |

## 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/bge_small_en_5.2.1_3.0_1704105455110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_en_5.2.1_3.0_1704105455110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

## How to use



<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
document = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")

embeddings = BGEEmbeddings.pretrained("bge_small", "en")\
.setInputCols("document")\
.setOutputCol("embeddings")
```
```scala
val document = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")

val embeddings = BGEEmbeddings.pretrained("bge_small", "en")
.setInputCols("document")
.setOutputCol("embeddings")
```
</div>

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|bge_small|
|Compatibility:|Spark NLP 5.2.1+|
|License:|Open Source|
|Edition:|Official|
|Input Labels:|[document]|
|Output Labels:|[bge]|
|Language:|en|
|Size:|79.8 MB|