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dleemiller
/
sts-bert-hash-nano

Text Ranking
sentence-transformers
Safetensors
English
bert_hash
cross-encoder
modernbert
sts
stsb
stsbenchmark-sts
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use dleemiller/sts-bert-hash-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use dleemiller/sts-bert-hash-nano with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("dleemiller/sts-bert-hash-nano", 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
sts-bert-hash-nano
4.86 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
dleemiller's picture
dleemiller
Update README.md
09ac0b9 verified 7 months ago
  • eval
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  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    6.1 kB
    Update README.md 7 months ago
  • config.json
    1.13 kB
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  • configuration_bert_hash.py
    340 Bytes
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  • model.safetensors
    3.88 MB
    xet
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  • modeling_bert_hash.py
    22.6 kB
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.41 kB
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  • vocab.txt
    232 kB
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