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mlx-community
/
Qwen3-Reranker-0.6B-4bit

Text Ranking
MLX
Safetensors
sentence-transformers
qwen3
reranker
4-bit precision
Model card Files Files and versions
xet
Community

Instructions to use mlx-community/Qwen3-Reranker-0.6B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use mlx-community/Qwen3-Reranker-0.6B-4bit with MLX:

    # Download the model from the Hub
    pip install huggingface_hub[hf_xet]
    
    huggingface-cli download --local-dir Qwen3-Reranker-0.6B-4bit mlx-community/Qwen3-Reranker-0.6B-4bit
  • sentence-transformers

    How to use mlx-community/Qwen3-Reranker-0.6B-4bit with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("mlx-community/Qwen3-Reranker-0.6B-4bit")
    
    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
  • Local Apps Settings
  • LM Studio
Qwen3-Reranker-0.6B-4bit
347 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
beshkenadze's picture
beshkenadze
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5f32454 verified 4 days ago
  • .gitattributes
    1.57 kB
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  • README.md
    1.89 kB
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  • chat_template.jinja
    741 Bytes
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  • config.json
    1.02 kB
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  • generation_config.json
    214 Bytes
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  • model.safetensors
    335 MB
    xet
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  • model.safetensors.index.json
    49.8 kB
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
    377 Bytes
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