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  1. .gitattributes +1 -0
  2. .gitignore +1 -0
  3. README.md +66 -0
  4. convert.py +11 -0
  5. pytorch_model.onnx +3 -0
  6. requirements.txt +4 -0
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ .venv
README.md ADDED
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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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+ ---
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+
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+ # ONNX version of sentence-transormers/all-MiniLM-L12-v2
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+
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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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+
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+ Check out the [main Metarank docs](https://docs.metarank.ai) on how to configure it.
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+
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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-L12-v2
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+ ```
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+
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+ ## Building the model
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+
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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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+
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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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+ ```
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+
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+ ## License
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+
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+ Apache 2.0
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+ from transformers import AutoTokenizer, AutoModel
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+ import torch
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+
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+ model = AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L12-v2")
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+ model.eval()
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+
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+ sample = torch.randint(low=0, high=1, size=(1,128))
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+ input = (sample, sample, sample)
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+
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+ torch.onnx.export(model, input, 'pytorch_model.onnx', export_params=True)
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+
pytorch_model.onnx ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:a504d31e57702a74fecf5c2d7df67fa9fcb5635baa2cd335ac74bc2cbdefcbdd
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+ size 133597269
requirements.txt ADDED
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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