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dleemiller
/
EttinX-nli-xxs

Text Classification
sentence-transformers
Safetensors
English
modernbert
cross-encoder
reranker
Generated from Trainer
dataset_size:942069
loss:PrecomputedDistillationLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use dleemiller/EttinX-nli-xxs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use dleemiller/EttinX-nli-xxs with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("dleemiller/EttinX-nli-xxs")
    
    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
EttinX-nli-xxs
71.1 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
dleemiller's picture
dleemiller
Update README.md
04ded68 verified 9 months ago
  • .gitattributes
    1.52 kB
    initial commit 9 months ago
  • README.md
    4.67 kB
    Update README.md 9 months ago
  • config.json
    1.54 kB
    Upload folder using huggingface_hub 9 months ago
  • model.safetensors
    67.5 MB
    xet
    Upload folder using huggingface_hub 9 months ago
  • special_tokens_map.json
    694 Bytes
    Upload folder using huggingface_hub 9 months ago
  • tokenizer.json
    3.58 MB
    Upload folder using huggingface_hub 9 months ago
  • tokenizer_config.json
    20.8 kB
    Upload folder using huggingface_hub 9 months ago