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kmack
/
YELP-Review_Classifier

Text Classification
Transformers
Safetensors
distilbert
Sentiment Analysis
Text Classification
BERT
Yelp Reviews
Fine-tuned
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use kmack/YELP-Review_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use kmack/YELP-Review_Classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="kmack/YELP-Review_Classifier")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("kmack/YELP-Review_Classifier")
    model = AutoModelForSequenceClassification.from_pretrained("kmack/YELP-Review_Classifier")
  • Notebooks
  • Google Colab
  • Kaggle
YELP-Review_Classifier
408 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
kmack's picture
kmack
Upload quantized_distilbert.pth with huggingface_hub
d1e16a2 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    3.44 kB
    Update README.md over 1 year ago
  • config.json
    856 Bytes
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  • model.safetensors
    268 MB
    xet
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  • quantized_distilbert.pth
    139 MB
    xet
    Upload quantized_distilbert.pth with huggingface_hub over 1 year ago
  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    1.23 kB
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  • vocab.txt
    232 kB
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