Add 2.6 prebuilt models to Machine Learning (#2988)
* Add 2.6 prebuilt models Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Add supported prebuilt models Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Quick formatting tweak Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Add Jeff's feedback Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Add some light editorial feedback Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Update _ml-commons-plugin/pretrained-models.md Co-authored-by: Nathan Bower <nbower@amazon.com> * Update _ml-commons-plugin/pretrained-models.md Co-authored-by: Nathan Bower <nbower@amazon.com> * Update _ml-commons-plugin/pretrained-models.md Co-authored-by: Nathan Bower <nbower@amazon.com> * Update _ml-commons-plugin/pretrained-models.md Co-authored-by: Nathan Bower <nbower@amazon.com> * Add editorial feedback Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Add experimental label. Use same as model-serving framework Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Add example API call Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Add one last piece of feedback Signed-off-by: Naarcha-AWS <naarcha@amazon.com> --------- Signed-off-by: Naarcha-AWS <naarcha@amazon.com> Co-authored-by: Nathan Bower <nbower@amazon.com>
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layout: default
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title: Model-serving framework
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has_children: true
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nav_order: 110
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nav_order: 50
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---
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# Model-serving framework
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@ -21,7 +21,7 @@ To upload a custom model to OpenSearch, you need to prepare it outside of your O
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### Model support
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As of OpenSearch 2.4, the model-serving framework only supports text embedding models without GPU acceleration.
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As of OpenSearch 2.6, the model-serving framework supports text embedding models.
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### Model format
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---
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layout: default
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title: Pretrained models
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parent: Model-serving framework
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nav_order: 120
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---
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The model-serving framework is an experimental feature. For updates on the progress of the model-serving framework, or if you want to leave feedback that could help improve the feature, join the discussion in the [Model-serving framework forum](https://forum.opensearch.org/t/feedback-machine-learning-model-serving-framework-experimental-release/11439).
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{: .warning}
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# Pretrained models
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The model-serving framework supports a variety of open-source pretrained models that can assist with a range of machine learning (ML) search and analytics use cases.
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## Uploading pretrained models
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To use a pretrained model in your OpenSearch cluster:
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1. Select the model you want to upload. For a list of pretrained models, see [supported pretrained models](#supported-pretrained-models).
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2. Upload the model using the [upload API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/model-serving-framework#upload-model-to-opensearch). Because a pretrained model originates from the ML Commons model repository, you only need to provide the `name`, `version`, and `model_format` in the upload API request.
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```
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POST /_plugins/_ml/models/_upload
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{
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"name": "huggingface/sentence-transformers/all-MiniLM-L12-v2",
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"version": "1.0.1",
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"model_format": "TORCH_SCRIPT"
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}
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```
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For more information on how to upload and use ML models, see [Model-serving framework]({{site.url}}{{site.baseurl}}/ml-commons-plugin/model-serving-framework).
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## Supported pretrained models
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The model-serving framework supports the following models, categorized by type. Although models with the same type will have similar use cases, each model has a different model size and performs differently depending on your cluster. For a comparison of the performances of some pretrained models, see the [sbert documentation](https://www.sbert.net/docs/pretrained_models.html#model-overview).
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### Sentence transformers
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Sentence transformer models map sentences and paragraphs across a dimensional dense vector space. The number of vectors depends on the model. Use these models for use cases such as clustering and semantic search.
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The following table provides a list of sentence transformer models and artifact links to download them:
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| **Model name** | **Vector dimensions** | **Torchscript artifact** | **ONNX artifact** |
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|---|---|---|---|
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| `sentence-transformers/all-distilroberta-v1` | 768-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-distilroberta-v1/1.0.1/torch_script/sentence-transformers_all-distilroberta-v1-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-distilroberta-v1/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-distilroberta-v1/1.0.1/onnx/sentence-transformers_all-distilroberta-v1-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-distilroberta-v1/1.0.1/onnx/config.json) |
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| `sentence-transformers/all-MiniLM-L6-v2` | 384-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-MiniLM-L12-v2/1.0.1/torch_script/sentence-transformers_all-MiniLM-L12-v2-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-distilroberta-v1/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-MiniLM-L12-v2/1.0.1/onnx/sentence-transformers_all-MiniLM-L12-v2-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-distilroberta-v1/1.0.1/onnx/config.json) |
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| `sentence-transformers/all-MiniLM-L12-v2` | 384-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-MiniLM-L6-v2/1.0.1/torch_script/sentence-transformers_all-MiniLM-L6-v2-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-MiniLM-L6-v2/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-MiniLM-L6-v2/1.0.1/onnx/sentence-transformers_all-MiniLM-L6-v2-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-MiniLM-L6-v2/1.0.1/onnx/config.json) |
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| `sentence-transformers/all-mpnet-base-v2` | 768-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-mpnet-base-v2/1.0.1/torch_script/sentence-transformers_all-mpnet-base-v2-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-mpnet-base-v2/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-mpnet-base-v2/1.0.1/onnx/sentence-transformers_all-mpnet-base-v2-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/all-mpnet-base-v2/1.0.1/onnx/config.json) |
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| `sentence-transformers/msmarco-distilbert-base-tas-b` | 768-dimensional dense vector space. Optimized for semantic search. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/msmarco-distilbert-base-tas-b/1.0.1/torch_script/sentence-transformers_msmarco-distilbert-base-tas-b-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/msmarco-distilbert-base-tas-b/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/msmarco-distilbert-base-tas-b/1.0.1/onnx/sentence-transformers_msmarco-distilbert-base-tas-b-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/msmarco-distilbert-base-tas-b/1.0.1/onnx/config.json) |
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| `sentence-transformers/multi-qa-MiniLM-L6-cos-v1` | 384-dimensional dense vector space. Designed for semantic search and trained on 215 million question/answer pairs. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/1.0.1/torch_script/sentence-transformers_multi-qa-MiniLM-L6-cos-v1-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/1.0.1/onnx/sentence-transformers_multi-qa-MiniLM-L6-cos-v1-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-MiniLM-L6-cos-v1/1.0.1/onnx/config.json) |
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| `sentence-transformers/multi-qa-mpnet-base-dot-v1` | 384-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-mpnet-base-dot-v1/1.0.1/torch_script/sentence-transformers_multi-qa-mpnet-base-dot-v1-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-mpnet-base-dot-v1/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-mpnet-base-dot-v1/1.0.1/onnx/sentence-transformers_multi-qa-mpnet-base-dot-v1-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/multi-qa-mpnet-base-dot-v1/1.0.1/onnx/config.json) |
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| `sentence-transformers/paraphrase-MiniLM-L3-v2` | 384-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-MiniLM-L3-v2/1.0.1/torch_script/sentence-transformers_paraphrase-MiniLM-L3-v2-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-MiniLM-L3-v2/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-MiniLM-L3-v2/1.0.1/onnx/sentence-transformers_paraphrase-MiniLM-L3-v2-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-MiniLM-L3-v2/1.0.1/onnx/config.json) |
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| `sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2` | 384-dimensional dense vector space. | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/1.0.1/torch_script/sentence-transformers_paraphrase-multilingual-MiniLM-L12-v2-1.0.1-torch_script.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/1.0.1/torch_script/config.json) | - [model_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/1.0.1/onnx/sentence-transformers_paraphrase-multilingual-MiniLM-L12-v2-1.0.1-onnx.zip)<br>- [config_url](https://artifacts.opensearch.org/models/ml-models/huggingface/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2/1.0.1/onnx/config.json) |
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