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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 / eval
334 Bytes
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  • 1 contributor
History: 1 commit
dleemiller's picture
dleemiller
Upload folder using huggingface_hub
497686f verified 8 months ago
  • CrossEncoderCorrelationEvaluator_sts-validation_results.csv
    334 Bytes
    Upload folder using huggingface_hub 8 months ago