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takehika
/
mdeberta-v3-en-wanli-nli

Zero-Shot Classification
Transformers
Safetensors
English
multilingual
deberta-v2
text-classification
nli
english
WANLI
Zero-Shot Classification
Model card Files Files and versions
xet
Community

Instructions to use takehika/mdeberta-v3-en-wanli-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use takehika/mdeberta-v3-en-wanli-nli with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-classification", model="takehika/mdeberta-v3-en-wanli-nli")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("takehika/mdeberta-v3-en-wanli-nli")
    model = AutoModelForSequenceClassification.from_pretrained("takehika/mdeberta-v3-en-wanli-nli")
  • Notebooks
  • Google Colab
  • Kaggle
mdeberta-v3-en-wanli-nli
1.14 GB
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  • 1 contributor
History: 10 commits
takehika's picture
takehika
Update README.md
6c8b5e1 verified 2 months ago
  • .gitattributes
    1.57 kB
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  • README.md
    3.08 kB
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  • added_tokens.json
    23 Bytes
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  • config.json
    1.11 kB
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  • model.safetensors
    1.12 GB
    xet
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  • special_tokens_map.json
    970 Bytes
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  • spm.model
    4.31 MB
    xet
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  • tokenizer.json
    16.3 MB
    xet
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  • tokenizer_config.json
    19.8 kB
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