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  This is a [sentence-transformers](https://www.SBERT.net) model. It maps questions and paragraphs 768-dimensional dense vectors and should be used for semantic search.
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  The model uses an [CamemBERT-L6](https://huggingface.co/antoinelouis/camembert-L6) backbone, which is a pruned version of the pre-trained [CamemBERT](https://huggingface.co/camembert-base)
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- checkpoint with 40% less parameters, obtained by [dropping the top-layers](https://doi.org/10.48550/arXiv.2004.03844) from the original model.
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  The model was trained on the **French** portion of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) retrieval dataset.
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  ## Usage
 
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  This is a [sentence-transformers](https://www.SBERT.net) model. It maps questions and paragraphs 768-dimensional dense vectors and should be used for semantic search.
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  The model uses an [CamemBERT-L6](https://huggingface.co/antoinelouis/camembert-L6) backbone, which is a pruned version of the pre-trained [CamemBERT](https://huggingface.co/camembert-base)
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+ checkpoint with 38% less parameters, obtained by [dropping the top-layers](https://doi.org/10.48550/arXiv.2004.03844) from the original model.
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  The model was trained on the **French** portion of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) retrieval dataset.
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  ## Usage