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  # Cross-Encoder for MS Marco - ONNX
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- ONNX versions of [Sentence Transformers Cross Encoders](https://huggingface.co/cross-encoder).
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  The models were trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
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- The models can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. See [SBERT.net Retrieve & Re-rank](https://www.sbert.net/examples/applications/retrieve_rerank/README.html) for more details. The training code is available here: [SBERT.net Training MS Marco](https://github.com/UKPLab/sentence-transformers/tree/master/examples/training/ms_marco)
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  ## Models Available
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  # Cross-Encoder for MS Marco - ONNX
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+ ONNX versions of [Sentence Transformers Cross Encoders](https://huggingface.co/cross-encoder) to allow ranking without heavy dependencies.
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  The models were trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
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+ The models can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. See [SBERT.net Retrieve & Re-rank](https://www.sbert.net/examples/applications/retrieve_rerank/README.html) for more details.
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  ## Models Available
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