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HARSHU550
/
Sentiments

Text Classification
Transformers
PyTorch
google-tensorflow TensorFlow
Rust
Safetensors
English
distilbert
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use HARSHU550/Sentiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use HARSHU550/Sentiments with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="HARSHU550/Sentiments")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("HARSHU550/Sentiments")
    model = AutoModelForSequenceClassification.from_pretrained("HARSHU550/Sentiments")
  • Notebooks
  • Google Colab
  • Kaggle
Sentiments
1.07 GB
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  • 1 contributor
History: 4 commits
HARSHU550's picture
HARSHU550
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  • .gitattributes
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  • README.md
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  • config.json
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  • map.jpeg
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  • model.safetensors
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  • pytorch_model (1).bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    268 MB
    xet
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  • rust_model.ot
    268 MB
    xet
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  • tf_model.h5
    268 MB
    xet
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  • tokenizer_config.json
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  • vocab.txt
    262 kB
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