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voIsung
/
bge-reranker-jd-cv

Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:4368
loss:BinaryCrossEntropyLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use voIsung/bge-reranker-jd-cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use voIsung/bge-reranker-jd-cv with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("voIsung/bge-reranker-jd-cv")
    
    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
bge-reranker-jd-cv
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
voIsung's picture
voIsung
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8a8e095 verified 4 months ago
  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
    1.11 GB
    xet
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  • tokenizer.json
    16.8 MB
    xet
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  • tokenizer_config.json
    395 Bytes
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