content.raw: I've just stumbled upon some excellent work on (🇫🇷 French) retrieval models by 
content.type: text
content.value: I've just stumbled upon some excellent work on (🇫🇷 French) retrieval models by 
content.raw: @antoinelouis
content.type: mention
content.user: antoinelouis
content.raw: . Kudos to him! 
content.type: text
content.value: . Kudos to him! 
content.type: new_line
content.type: new_line
content.raw: - French Embedding Models: 
content.type: text
content.value: - French Embedding Models: 
content.href: https://huggingface.co/collections/antoinelouis/dense-single-vector-bi-encoders-651523c0c75a3d4c44fc864d
content.raw: https://huggingface.co/collections/antoinelouis/dense-single-vector-bi-encoders-651523c0c75a3d4c44fc864d
content.type: link
content.type: new_line
content.raw: - French Reranker Models: 
content.type: text
content.value: - French Reranker Models: 
content.raw: https://huggingface.co/collections/antoinelouis/cross-encoder-rerankers-651523f16efa656d1788a239
content.id: antoinelouis/cross-encoder-rerankers-651523f16efa656d1788a239
content.type: collection
content.type: resource
content.url: https://huggingface.co/collections/antoinelouis/cross-encoder-rerankers-651523f16efa656d1788a239
content.type: new_line
content.raw: - French Multi-vector Models: 
content.type: text
content.value: - French Multi-vector Models: 
content.href: https://huggingface.co/collections/antoinelouis/dense-multi-vector-bi-encoders-6589a8ee6b17c06872e9f075
content.raw: https://huggingface.co/collections/antoinelouis/dense-multi-vector-bi-encoders-6589a8ee6b17c06872e9f075
content.type: link
content.type: new_line
content.raw: - Multilingual Models: 
content.type: text
content.value: - Multilingual Models: 
content.href: https://huggingface.co/collections/antoinelouis/modular-retrievers-65d53d0db64b1d644aea620c
content.raw: https://huggingface.co/collections/antoinelouis/modular-retrievers-65d53d0db64b1d644aea620c
content.type: link
content.type: new_line
content.type: new_line
content.raw: A lot of these models use the MS MARCO Hard Negatives dataset, which I'm currently reformatting to be more easily usable. Notably, they should work out of the box without any pre-processing for training embedding models in the upcoming Sentence Transformers v3.
content.type: text
content.value: A lot of these models use the MS MARCO Hard Negatives dataset, which I'm currently reformatting to be more easily usable. Notably, they should work out of the box without any pre-processing for training embedding models in the upcoming Sentence Transformers v3.
rawContent: I've just stumbled upon some excellent work on (🇫🇷 French) retrieval models by @antoinelouis. Kudos to him! 
  
  - French Embedding Models: https://huggingface.co/collections/antoinelouis/dense-single-vector-bi-encoders-651523c0c75a3d4c44fc864d
  - French Reranker Models: https://huggingface.co/collections/antoinelouis/cross-encoder-rerankers-651523f16efa656d1788a239
  - French Multi-vector Models: https://huggingface.co/collections/antoinelouis/dense-multi-vector-bi-encoders-6589a8ee6b17c06872e9f075
  - Multilingual Models: https://huggingface.co/collections/antoinelouis/modular-retrievers-65d53d0db64b1d644aea620c
  
  A lot of these models use the MS MARCO Hard Negatives dataset, which I'm currently reformatting to be more easily usable. Notably, they should work out of the box without any pre-processing for training embedding models in the upcoming Sentence Transformers v3.
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