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Quintu
/
roberta-large-768-hazard

Text Classification
Transformers
Safetensors
English
roberta
hazard-detection
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Quintu/roberta-large-768-hazard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Quintu/roberta-large-768-hazard with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Quintu/roberta-large-768-hazard")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Quintu/roberta-large-768-hazard")
    model = AutoModelForSequenceClassification.from_pretrained("Quintu/roberta-large-768-hazard")
  • Notebooks
  • Google Colab
  • Kaggle
roberta-large-768-hazard
1.42 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
Quintu's picture
Quintu
Update README.md
7ba36ca verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    1.03 kB
    Update README.md over 1 year ago
  • config.json
    1.25 kB
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  • model.safetensors
    1.42 GB
    xet
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  • rng_state.pth

    Detected Pickle imports (7)

    • "numpy.ndarray",
    • "numpy.core.multiarray._reconstruct",
    • "torch.ByteStorage",
    • "_codecs.encode",
    • "numpy.dtype",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2"

    How to fix it?

    14.2 kB
    xet
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  • scheduler.pt

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    1.06 kB
    xet
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    2.11 MB
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  • tokenizer_config.json
    1.22 kB
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  • trainer_state.json
    103 kB
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  • training_args.bin
    5.24 kB
    xet
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  • vocab.json
    798 kB
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