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nlpai-lab
/
KURE-Reranker-nano

Text Ranking
sentence-transformers
Safetensors
Korean
English
modernbert
cross-encoder
reranker
korean
english
text-embeddings-inference
Model card Files Files and versions
xet
Community
3

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

  • Libraries
  • sentence-transformers

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

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("nlpai-lab/KURE-Reranker-nano")
    
    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)
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
KURE-Reranker-nano / assets
1.12 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
yjoonjang's picture
yjoonjang
Move the figure legend slightly left of the x=1000 tick
725a83c verified 20 days ago
  • kure_logo.png
    594 kB
    xet
    init about 1 month ago
  • pps_performance_2col.png
    206 kB
    xet
    init about 1 month ago
  • pps_vs_ndcg9.png
    113 kB
    xet
    Move the figure legend slightly left of the x=1000 tick 20 days ago
  • size_performance_2col.png
    211 kB
    xet
    init about 1 month ago