add readme and model card
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- requirements.txt +2 -1
README.md
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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 sentence-transormers/all-MiniLM-L6-v2
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This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. The ONNX version of this model is made for the [Metarank](https://github.com/metarank/metarank) re-ranker
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to do semantic similarity.
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Check out the [main Metarank docs](https://docs.metarank.ai) on how to configure it.
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TLDR:
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```yaml
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- type: field_match
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name: title_query_match
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rankingField: ranking.query
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itemField: item.title
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distance: cos
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method:
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type: bert
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model: metarank/all-MiniLM-L6-v2
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```
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## Building the model
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```shell
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$> pip install -r requirements.txt
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$> python convert.py
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============= Diagnostic Run torch.onnx.export version 2.0.0+cu117 =============
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verbose: False, log level: Level.ERROR
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======================= 0 NONE 0 NOTE 0 WARNING 0 ERROR ========================
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```
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## License
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Apache 2.0
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requirements.txt
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sentence-transformers==2.2.2
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torch==2.0.0
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onnx
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sentence-transformers==2.2.2
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torch==2.0.0
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onnx==1.13.1
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huggingface_hub==0.13.3
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