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OverSamu
/
reranker-sapbert-ncbi-disease-bce-context

Text Ranking
sentence-transformers
Safetensors
English
bert
cross-encoder
reranker
Generated from Trainer
dataset_size:222348
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use OverSamu/reranker-sapbert-ncbi-disease-bce-context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use OverSamu/reranker-sapbert-ncbi-disease-bce-context with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("OverSamu/reranker-sapbert-ncbi-disease-bce-context")
    
    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
reranker-sapbert-ncbi-disease-bce-context
439 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
OverSamu's picture
OverSamu
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  • .gitattributes
    1.52 kB
    initial commit 5 months ago
  • README.md
    16.8 kB
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  • config.json
    827 Bytes
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  • model.safetensors
    438 MB
    xet
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    706 kB
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  • tokenizer_config.json
    1.3 kB
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  • vocab.txt
    226 kB
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