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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
3.45 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
yjoonjang's picture
yjoonjang
Retrained with fp32 master weights: 0.8908 mean nDCG@10 on the nine Korean tasks (was 0.8800)
0ca2319 verified 2 days ago
  • 1_LogitScore
    Add new CrossEncoder model about 1 month ago
  • assets
    Retrained with fp32 master weights: 0.8908 mean nDCG@10 on the nine Korean tasks (was 0.8800) 2 days ago
  • .gitattributes
    1.69 kB
    Update KURE-Reranker-base weights (bf16), model card and assets 24 days ago
  • README.md
    23.5 kB
    Retrained with fp32 master weights: 0.8908 mean nDCG@10 on the nine Korean tasks (was 0.8800) 2 days ago
  • chat_template.jinja
    741 Bytes
    Add new CrossEncoder model about 1 month ago
  • config.json
    1.42 kB
    Add new CrossEncoder model about 1 month ago
  • config_sentence_transformers.json
    258 Bytes
    Add new CrossEncoder model about 1 month ago
  • generation_config.json
    214 Bytes
    Add new CrossEncoder model about 1 month ago
  • model.safetensors
    3.44 GB
    xet
    Retrained with fp32 master weights: 0.8908 mean nDCG@10 on the nine Korean tasks (was 0.8800) 2 days ago
  • modules.json
    280 Bytes
    Add new CrossEncoder model about 1 month ago
  • sentence_bert_config.json
    362 Bytes
    Add new CrossEncoder model about 1 month ago
  • tokenizer.json
    11.4 MB
    xet
    Add new CrossEncoder model about 1 month ago
  • tokenizer_config.json
    882 Bytes
    Add new CrossEncoder model about 1 month ago