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shawnw3i
/
Qwen3-Reranker-4B-seq-cls-ONNX

Text Ranking
sentence-transformers
ONNX
Transformers
qwen3
text-classification
Model card Files Files and versions
xet
Community
1

Instructions to use shawnw3i/Qwen3-Reranker-4B-seq-cls-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use shawnw3i/Qwen3-Reranker-4B-seq-cls-ONNX with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("shawnw3i/Qwen3-Reranker-4B-seq-cls-ONNX")
    
    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)
  • Transformers

    How to use shawnw3i/Qwen3-Reranker-4B-seq-cls-ONNX with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("shawnw3i/Qwen3-Reranker-4B-seq-cls-ONNX")
    model = AutoModelForSequenceClassification.from_pretrained("shawnw3i/Qwen3-Reranker-4B-seq-cls-ONNX")
  • Notebooks
  • Google Colab
  • Kaggle
Qwen3-Reranker-4B-seq-cls-ONNX
8.06 GB
Ctrl+K
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  • 1 contributor
History: 3 commits
zhiqing
Create README.md
0730823 verified 11 months ago
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  • README.md
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  • added_tokens.json
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  • chat_template.jinja
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  • config.json
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  • merges.txt
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  • model.onnx
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  • model.onnx_data
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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