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OloriBern
/
bge-m3-musique-hybrid-3ep

Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:6310
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use OloriBern/bge-m3-musique-hybrid-3ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use OloriBern/bge-m3-musique-hybrid-3ep with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("OloriBern/bge-m3-musique-hybrid-3ep")
    
    query = "Which planet is known as the Red Planet?"
    passages = [
    	"Venus is often called Earth's twin because of its similar size and proximity.",
    	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
    	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
    	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
    ]
    
    scores = model.predict([(query, passage) for passage in passages])
    print(scores)
  • Notebooks
  • Google Colab
  • Kaggle
bge-m3-musique-hybrid-3ep
2.29 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
OloriBern's picture
OloriBern
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  • eval
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  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
    2.27 GB
    xet
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    1.4 kB
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