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andrewma5
/
harvard-loop-reranker

Text Ranking
sentence-transformers
Safetensors
bert
cross-encoder
reranker
Generated from Trainer
dataset_size:114138
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use andrewma5/harvard-loop-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use andrewma5/harvard-loop-reranker with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("andrewma5/harvard-loop-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
harvard-loop-reranker
91.8 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
andrewma5's picture
andrewma5
Initial model upload
909e6ca verified 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • README.md
    16.7 kB
    Initial model upload 6 months ago
  • config.json
    823 Bytes
    Initial model upload 6 months ago
  • model.safetensors
    90.9 MB
    xet
    Initial model upload 6 months ago
  • special_tokens_map.json
    695 Bytes
    Initial model upload 6 months ago
  • tokenizer.json
    712 kB
    Initial model upload 6 months ago
  • tokenizer_config.json
    1.27 kB
    Initial model upload 6 months ago
  • vocab.txt
    232 kB
    Initial model upload 6 months ago