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pitangent-ds
/
deberta-v3-nli-onnx-quantized

Zero-Shot Classification
Transformers
ONNX
English
deberta-v2
text-classification
ORTModelForSequenceClassification
Model card Files Files and versions
xet
Community

Instructions to use pitangent-ds/deberta-v3-nli-onnx-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use pitangent-ds/deberta-v3-nli-onnx-quantized with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-classification", model="pitangent-ds/deberta-v3-nli-onnx-quantized")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("pitangent-ds/deberta-v3-nli-onnx-quantized")
    model = AutoModelForSequenceClassification.from_pretrained("pitangent-ds/deberta-v3-nli-onnx-quantized", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
deberta-v3-nli-onnx-quantized
256 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 19 commits
arnabdhar's picture
arnabdhar
Update README.md
b9df927 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    1.55 kB
    Update README.md about 2 years ago
  • added_tokens.json
    23 Bytes
    Upload added_tokens.json with huggingface_hub about 2 years ago
  • config.json
    18.5 kB
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  • model_quantized.onnx
    244 MB
    xet
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  • ort_config.json
    763 Bytes
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  • special_tokens_map.json
    970 Bytes
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  • spm.model
    2.46 MB
    xet
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  • tokenizer.json
    8.65 MB
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  • tokenizer_config.json
    1.48 kB
    Upload tokenizer_config.json with huggingface_hub about 2 years ago