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ThienLe
/
Qwen3-SecRerank

Text Ranking
sentence-transformers
Safetensors
qwen3
cross-encoder
reranker
Generated from Trainer
dataset_size:49346
loss:CachedMultipleNegativesRankingLoss
Model card Files Files and versions
xet
Community

Instructions to use ThienLe/Qwen3-SecRerank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ThienLe/Qwen3-SecRerank with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("ThienLe/Qwen3-SecRerank")
    
    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
Qwen3-SecRerank
2.39 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
ThienLe's picture
ThienLe
Add new CrossEncoder model
8aaa77b verified 3 months ago
  • .gitattributes
    1.57 kB
    Add new CrossEncoder model 3 months ago
  • README.md
    48.1 kB
    Add new CrossEncoder model 3 months ago
  • config.json
    1.63 kB
    Add new CrossEncoder model 3 months ago
  • model.safetensors
    2.38 GB
    xet
    Add new CrossEncoder model 3 months ago
  • tokenizer.json
    11.4 MB
    xet
    Add new CrossEncoder model 3 months ago
  • tokenizer_config.json
    346 Bytes
    Add new CrossEncoder model 3 months ago