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cometadata
/
ms-marco-ror-reranker

Text Classification
sentence-transformers
Safetensors
English
multilingual
bert
cross-encoder
reranker
ror
affiliation-matching
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use cometadata/ms-marco-ror-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use cometadata/ms-marco-ror-reranker with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("cometadata/ms-marco-ror-reranker")
    
    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
ms-marco-ror-reranker
Ctrl+K
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  • 1 contributor
History: 3 commits
adambuttrick's picture
adambuttrick
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4a9ddc6 verified 4 months ago
  • eval
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  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    1.68 kB
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  • config.json
    824 Bytes
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  • model.safetensors
    133 MB
    xet
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.27 kB
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  • vocab.txt
    232 kB
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