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nlpai-lab
/
KURE-Reranker-base

Text Ranking
sentence-transformers
Safetensors
Korean
English
qwen3
cross-encoder
reranker
korean
english
Model card Files Files and versions
xet
Community

Instructions to use nlpai-lab/KURE-Reranker-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use nlpai-lab/KURE-Reranker-base with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("nlpai-lab/KURE-Reranker-base")
    
    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
KURE-Reranker-base / assets
707 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
yjoonjang's picture
yjoonjang
Move the figure legend slightly left of the x=1000 tick
815f7d4 verified about 2 hours ago
  • kure_logo.png
    594 kB
    xet
    Update KURE-Reranker-base weights (bf16), model card and assets about 3 hours ago
  • pps_vs_ndcg9.png
    113 kB
    xet
    Move the figure legend slightly left of the x=1000 tick about 2 hours ago