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zeroentropy
/
zerank-1

Text Ranking
sentence-transformers
Safetensors
English
qwen3
finance
legal
code
stem
medical
custom_code
Model card Files Files and versions
xet
Community
6

Instructions to use zeroentropy/zerank-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use zeroentropy/zerank-1 with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("zeroentropy/zerank-1", trust_remote_code=True)
    
    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
zerank-1
8.06 GB
Ctrl+K
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  • 5 contributors
History: 17 commits
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dilawarm
Update README.md
9c84845 verified about 2 months ago
  • .gitattributes
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  • added_tokens.json
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • model-00001-of-00002.safetensors
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  • model-00002-of-00002.safetensors
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  • model.safetensors.index.json
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  • modeling_zeranker.py
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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