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lewtun
/
quantized-distilbert-banking77

Text Classification
Transformers
ONNX
optimum
Eval Results (legacy)
Model card Files Files and versions
xet
Community
2

Instructions to use lewtun/quantized-distilbert-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use lewtun/quantized-distilbert-banking77 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="lewtun/quantized-distilbert-banking77")
    # Load model directly
    from transformers import AutoModelForSequenceClassification
    model = AutoModelForSequenceClassification.from_pretrained("lewtun/quantized-distilbert-banking77", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
quantized-distilbert-banking77
269 MB
Ctrl+K
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  • 1 contributor
History: 27 commits
lewtun's picture
lewtun HF Staff
Upload special_tokens_map.json with huggingface_hub
93f4247 over 3 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • README.md
    1.79 kB
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  • config.json
    5.78 kB
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  • model.onnx
    268 MB
    xet
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  • special_tokens_map.json
    125 Bytes
    Upload special_tokens_map.json with huggingface_hub over 3 years ago
  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    341 Bytes
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  • vocab.txt
    232 kB
    Upload vocab.txt almost 4 years ago