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Hizlan
/
ciso-cross-encoder

Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:628
loss:FitMixinLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Hizlan/ciso-cross-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Hizlan/ciso-cross-encoder with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Hizlan/ciso-cross-encoder")
    
    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
ciso-cross-encoder
493 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Hizlan's picture
Hizlan
2nd finetuned-version
2bf225f 9 months ago
  • .gitattributes
    1.57 kB
    Upload 7 files 10 months ago
  • README.md
    15.9 kB
    2nd finetuned-version 9 months ago
  • config.json
    851 Bytes
    2nd finetuned-version 9 months ago
  • model.safetensors
    471 MB
    xet
    2nd finetuned-version 9 months ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    Upload 7 files 10 months ago
  • special_tokens_map.json
    964 Bytes
    Upload 7 files 10 months ago
  • tokenizer.json
    17.1 MB
    xet
    Upload 7 files 10 months ago
  • tokenizer_config.json
    1.18 kB
    Upload 7 files 10 months ago