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eazzy
/
klue-roberta-small-crossencoder

Text Ranking
sentence-transformers
Safetensors
roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:35108
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use eazzy/klue-roberta-small-crossencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use eazzy/klue-roberta-small-crossencoder with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("eazzy/klue-roberta-small-crossencoder")
    
    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
klue-roberta-small-crossencoder
273 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
eazzy's picture
eazzy
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28376c3 verified 7 months ago
  • .gitattributes
    1.52 kB
    initial commit 7 months ago
  • README.md
    49.5 kB
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  • config.json
    1.61 kB
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  • model.safetensors
    272 MB
    xet
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  • special_tokens_map.json
    971 Bytes
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  • tokenizer.json
    752 kB
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  • tokenizer_config.json
    1.31 kB
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  • vocab.txt
    248 kB
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