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BSC-NLP4BIA
/
Medprocner-CE-Reranker

Text Ranking
sentence-transformers
Safetensors
roberta
cross-encoder
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use BSC-NLP4BIA/Medprocner-CE-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use BSC-NLP4BIA/Medprocner-CE-Reranker with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("BSC-NLP4BIA/Medprocner-CE-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
Medprocner-CE-Reranker
509 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
abecerr1's picture
abecerr1
Add new CrossEncoder model
b81d321 verified 11 months ago
  • .gitattributes
    1.52 kB
    initial commit 11 months ago
  • README.md
    3.86 kB
    Add new CrossEncoder model 11 months ago
  • config.json
    881 Bytes
    Add new CrossEncoder model 11 months ago
  • merges.txt
    540 kB
    Add new CrossEncoder model 11 months ago
  • model.safetensors
    504 MB
    xet
    Add new CrossEncoder model 11 months ago
  • special_tokens_map.json
    957 Bytes
    Add new CrossEncoder model 11 months ago
  • tokenizer.json
    3.82 MB
    Add new CrossEncoder model 11 months ago
  • tokenizer_config.json
    1.45 kB
    Add new CrossEncoder model 11 months ago
  • vocab.json
    894 kB
    Add new CrossEncoder model 11 months ago