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--- |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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language: en |
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license: apache-2.0 |
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datasets: |
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- s2orc |
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- flax-sentence-embeddings/stackexchange_xml |
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- ms_marco |
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- gooaq |
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- yahoo_answers_topics |
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- code_search_net |
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- search_qa |
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- eli5 |
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- snli |
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- multi_nli |
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- wikihow |
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- natural_questions |
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- trivia_qa |
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- embedding-data/sentence-compression |
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- embedding-data/flickr30k-captions |
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- embedding-data/altlex |
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- embedding-data/simple-wiki |
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- embedding-data/QQP |
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- embedding-data/SPECTER |
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- embedding-data/PAQ_pairs |
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- embedding-data/WikiAnswers |
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--- |
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# ONNX version of intfloat/multilingual-e5-large |
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This is a sentence-transformers model: It maps sentences & paragraphs to a N dimensional dense vector space and can be used for tasks like clustering or semantic search. |
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The model conversion was made with [onnx-convert](https://github.com/nixiesearch/onnx-convert) tool with the following parameters: |
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```shell |
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python convert.sh --model_id intfloat/multilingual-e5-large --quantize QInt8 --optimize 0 |
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``` |
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There are two versions of model available: |
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* `model.onnx` - Float32 version, with optimize=0 |
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* `model_opt0_QInt8.onnx` - QInt8 quantized version, with optimize=0 |
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Compared to the base/small versions of the model, this one is not optimized due to a bug in ONNX runtime: https://github.com/microsoft/onnxruntime/issues/15563 |
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## License |
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Apache 2.0 |
