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muvon
/
octomind-rerank

sentence-transformers
ONNX
Safetensors
xlm-roberta
cross-encoder
octomind
reranker
bert
Model card Files Files and versions
xet
Community

Instructions to use muvon/octomind-rerank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use muvon/octomind-rerank with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("muvon/octomind-rerank")
    
    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
octomind-rerank / eval
329 Bytes
Ctrl+K
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  • 1 contributor
History: 3 commits
donk8r's picture
donk8r
Upload folder using huggingface_hub
3daaed1 verified 3 months ago
  • CrossEncoderClassificationEvaluator_rerank-holdout_results.csv
    329 Bytes
    Upload folder using huggingface_hub 3 months ago