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olaverse
/
mist-reranker-150m

Text Ranking
sentence-transformers
Safetensors
English
modernbert
reranker
cross-encoder
retrieval
RAG
mist
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use olaverse/mist-reranker-150m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use olaverse/mist-reranker-150m with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("olaverse/mist-reranker-150m")
    
    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
mist-reranker-150m
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
olumideola's picture
olumideola
Update README.md
b4d1bd4 verified 20 days ago
  • .gitattributes
    1.52 kB
    initial commit 20 days ago
  • README.md
    4.63 kB
    Update README.md 20 days ago
  • config.json
    1.42 kB
    Add new CrossEncoder model 20 days ago
  • model.safetensors
    598 MB
    xet
    Add new CrossEncoder model 20 days ago
  • special_tokens_map.json
    694 Bytes
    Add new CrossEncoder model 20 days ago
  • tokenizer.json
    3.58 MB
    Add new CrossEncoder model 20 days ago
  • tokenizer_config.json
    20.8 kB
    Add new CrossEncoder model 20 days ago