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zeroshot
/
sst2-distilbert-dense

Text Classification
Transformers
ONNX
distilbert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use zeroshot/sst2-distilbert-dense with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use zeroshot/sst2-distilbert-dense with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="zeroshot/sst2-distilbert-dense")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("zeroshot/sst2-distilbert-dense")
    model = AutoModelForSequenceClassification.from_pretrained("zeroshot/sst2-distilbert-dense")
  • Notebooks
  • Google Colab
  • Kaggle
sst2-distilbert-dense
269 MB
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  • 2 contributors
History: 7 commits
zeroshot's picture
zeroshot
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6013fd3 over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    501 Bytes
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  • config.json
    795 Bytes
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  • handler.py
    711 Bytes
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  • model.onnx
    268 MB
    xet
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  • requirements.txt
    17 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    392 Bytes
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