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NDugar
/
2epochv3mlni

Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Model card Files Files and versions
xet
Community
1

Instructions to use NDugar/2epochv3mlni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NDugar/2epochv3mlni with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-classification", model="NDugar/2epochv3mlni")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("NDugar/2epochv3mlni")
    model = AutoModelForSequenceClassification.from_pretrained("NDugar/2epochv3mlni", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
2epochv3mlni
2.49 MB
Ctrl+K
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  • 2 contributors
History: 10 commits
NDugar's picture
NDugar
Upload tokenizer_config.json
c7074f6 over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    4.79 kB
    Create README.md over 4 years ago
  • added_tokens.json
    18 Bytes
    Upload added_tokens.json over 4 years ago
  • config.json
    1.06 kB
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  • rng_state.pth
    14.5 kB
    xet
    Upload rng_state.pth with git-lfs over 4 years ago
  • scaler.pt
    559 Bytes
    xet
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  • scheduler.pt
    623 Bytes
    xet
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  • special_tokens_map.json
    156 Bytes
    Upload special_tokens_map.json over 4 years ago
  • spm.model
    2.46 MB
    xet
    Upload spm.model with git-lfs over 4 years ago
  • tokenizer_config.json
    418 Bytes
    Upload tokenizer_config.json over 4 years ago