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software-si
/
kitchen-nli

Text Classification
sentence-transformers
Safetensors
English
deberta-v2
cross-encoder
reranker
Generated from Trainer
dataset_size:102836
loss:CrossEntropyLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use software-si/kitchen-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use software-si/kitchen-nli with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("software-si/kitchen-nli")
    
    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
kitchen-nli
746 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
software-si's picture
software-si
Update README.md
83ebf38 verified 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    14.5 kB
    Update README.md 6 months ago
  • config.json
    1.17 kB
    Add new CrossEncoder model 8 months ago
  • model.safetensors
    738 MB
    xet
    Add new CrossEncoder model 8 months ago
  • special_tokens_map.json
    970 Bytes
    Add new CrossEncoder model 8 months ago
  • tokenizer.json
    8.65 MB
    Add new CrossEncoder model 8 months ago
  • tokenizer_config.json
    1.29 kB
    Add new CrossEncoder model 8 months ago