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dleemiller
/
ModernCE-large-nli

Text Classification
sentence-transformers
Safetensors
English
modernbert
cross-encoder
mnli
snli
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use dleemiller/ModernCE-large-nli with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("dleemiller/ModernCE-large-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
ModernCE-large-nli
1.59 GB
Ctrl+K
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  • 1 contributor
History: 7 commits
dleemiller's picture
dleemiller
Update README.md
0c0575b verified 7 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • CESoftmaxAccuracyEvaluator_AllNLI-dev_results.csv
    448 Bytes
    Upload 6 files about 1 year ago
  • README.md
    4.3 kB
    Update README.md 7 months ago
  • config.json
    5.58 kB
    Upload 6 files about 1 year ago
  • model.safetensors
    1.58 GB
    xet
    Upload 6 files about 1 year ago
  • special_tokens_map.json
    694 Bytes
    Upload 6 files about 1 year ago
  • tokenizer.json
    3.58 MB
    Upload 6 files about 1 year ago
  • tokenizer_config.json
    21.1 kB
    Upload 6 files about 1 year ago