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Muzian
/
minimind-rerank-dense

Text Ranking
sentence-transformers
Safetensors
Chinese
English
minimind
cross-encoder
reranker
rerank
chinese
qwen3-reranker
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use Muzian/minimind-rerank-dense with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Muzian/minimind-rerank-dense")
    
    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
minimind-rerank-dense
139 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
Muzian's picture
Muzian
Add model card: training curves + MAP@10 evolution + Three Bugs story
2720afe verified 12 days ago
  • images
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  • .gitattributes
    1.64 kB
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  • README.md
    5.18 kB
    Add model card: training curves + MAP@10 evolution + Three Bugs story 12 days ago
  • config.json
    529 Bytes
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  • model.safetensors
    138 MB
    xet
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  • tokenizer.json
    482 kB
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  • tokenizer_config.json
    13.6 kB
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