crossencoder camembert base mmarcoFR This is a cross encoder model for French. It performs cross attention between a question passage pair and outputs a relevance score. The model should be used as a reranker for semantic search: given a query and a set of potentially relevant passages retrieved by an efficient first stage retrieval system (e.g., BM25 or a fine tuned dense single vector bi encoder), encode each query passage pair and sort the passages in a decreasing order of relevance according to the model's predicted scores. Usage Here are some examples for using the model with Sentence Transformers, FlagEmbedding, or Huggingface Transformers. Using Sentence Transformers Start by installing the library: pip install U sentence transformers . Then, you can use the model like this: Using FlagEmbedding Start by installing the library: pip install U FlagEmbedding . Then, you can use the model like this: Using HuggingFace Transformers Start by installing the library: pip install U transformers . Then, you can use the model like this: Evaluation The model is evaluated on the smaller development set of mMARCO fr, which consists of 6,980 queries for which an ensemble of 1000 passages con…
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