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optimum
/
distilbert-base-uncased-mnli

Zero-Shot Classification
Transformers
ONNX
English
text-classification
distilbert
Model card Files Files and versions
xet
Community

Instructions to use optimum/distilbert-base-uncased-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use optimum/distilbert-base-uncased-mnli with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-classification", model="optimum/distilbert-base-uncased-mnli")
    # Load model directly
    from transformers import AutoModelForSequenceClassification
    model = AutoModelForSequenceClassification.from_pretrained("optimum/distilbert-base-uncased-mnli", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
distilbert-base-uncased-mnli
269 MB
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  • 1 contributor
History: 8 commits
philschmid's picture
philschmid
Create README.md
f2a4115 over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    1.19 kB
    Create README.md over 4 years ago
  • config.json
    728 Bytes
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  • model.onnx
    268 MB
    xet
    Upload model.onnx with git-lfs over 4 years ago
  • special_tokens_map.json
    112 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    567 Bytes
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  • vocab.txt
    232 kB
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