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kirubelmidru
/
resume-cross-encoder

Text Classification
sentence-transformers
Safetensors
bert
cross-encoder
reranker
Generated from Trainer
dataset_size:6241
loss:CrossEntropyLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use kirubelmidru/resume-cross-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use kirubelmidru/resume-cross-encoder with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("kirubelmidru/resume-cross-encoder")
    
    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
resume-cross-encoder
91.6 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
kirubelmidru's picture
kirubelmidru
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a75bd09 verified about 2 months ago
  • .gitattributes
    1.52 kB
    initial commit about 2 months ago
  • README.md
    62.9 kB
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  • config.json
    765 Bytes
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  • config_sentence_transformers.json
    258 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
    453 Bytes
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