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Hanno-Labs
/
DeBERTa-v3-base-mnli-fever-docnli-ling-2c-onnx

Text Classification
Transformers
ONNX
English
optimum
deberta-v3
nli
natural-language-inference
zero-shot-classification
cross-encoder
Model card Files Files and versions
xet
Community

Instructions to use Hanno-Labs/DeBERTa-v3-base-mnli-fever-docnli-ling-2c-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Hanno-Labs/DeBERTa-v3-base-mnli-fever-docnli-ling-2c-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Hanno-Labs/DeBERTa-v3-base-mnli-fever-docnli-ling-2c-onnx")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Hanno-Labs/DeBERTa-v3-base-mnli-fever-docnli-ling-2c-onnx", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
DeBERTa-v3-base-mnli-fever-docnli-ling-2c-onnx / nli-onnx
785 MB
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  • 1 contributor
History: 1 commit
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stephen-solka
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  • added_tokens.json
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  • config.json
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  • model.onnx
    774 MB
    xet
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  • ort_config.json
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  • special_tokens_map.json
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  • spm.model
    2.46 MB
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  • tokenizer.json
    8.65 MB
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  • tokenizer_config.json
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