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cihatyldz
/
kalbur-reranker

Text Ranking
sentence-transformers
ONNX
Safetensors
Turkish
xlm-roberta
reranker
cross-encoder
turkish
robustness
distillation
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use cihatyldz/kalbur-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use cihatyldz/kalbur-reranker with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("cihatyldz/kalbur-reranker")
    
    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
kalbur-reranker
5.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
cihatyldz's picture
cihatyldz
Kart: int8 hız ifadesi düzeltildi
e60002a verified 2 days ago
  • onnx
    Model kartı + ONNX int8 2 days ago
  • .gitattributes
    1.63 kB
    Model kartı + ONNX int8 2 days ago
  • README.md
    7.98 kB
    Kart: int8 hız ifadesi düzeltildi 2 days ago
  • config.json
    842 Bytes
    Kalbur: adım 1050 3 days ago
  • kalbur_training.json
    4.48 kB
    Kalbur: adım 1050 3 days ago
  • model.safetensors
    2.27 GB
    xet
    Kalbur: adım 1050 3 days ago
  • tokenizer.json
    17.1 MB
    xet
    Kalbur: adım 1050 3 days ago
  • tokenizer_config.json
    409 Bytes
    Kalbur: adım 1050 3 days ago