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Amdestya
/
ce-bm25cat-distilbert

Text Ranking
sentence-transformers
Safetensors
English
distilbert
cross-encoder
reranker
msmarco
bm25-injection
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Amdestya/ce-bm25cat-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Amdestya/ce-bm25cat-distilbert with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Amdestya/ce-bm25cat-distilbert")
    
    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
ce-bm25cat-distilbert
269 MB
Ctrl+K
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  • 1 contributor
History: 5 commits
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Amdestya
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  • .gitattributes
    1.52 kB
    initial commit 6 days ago
  • README.md
    2.15 kB
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  • USAGE.json
    1.17 kB
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  • config.json
    592 Bytes
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  • model.safetensors
    268 MB
    xet
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.23 kB
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  • vocab.txt
    232 kB
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