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ChengyouXin
/
cacheverifier-quora

Text Ranking
sentence-transformers
Safetensors
bert
cross-encoder
reranker
Generated from Trainer
dataset_size:11928
loss:BinaryCrossEntropyLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ChengyouXin/cacheverifier-quora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ChengyouXin/cacheverifier-quora with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("ChengyouXin/cacheverifier-quora")
    
    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
cacheverifier-quora
91.6 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
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ChengyouXin
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  • .gitattributes
    1.52 kB
    initial commit 2 days ago
  • README.md
    14.5 kB
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  • config.json
    844 Bytes
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  • config_sentence_transformers.json
    259 Bytes
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  • model.safetensors
    90.9 MB
    xet
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  • modules.json
    131 Bytes
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  • sentence_bert_config.json
    225 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    442 Bytes
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