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MilaNLProc
/
hate-ita

Text Classification
Transformers
PyTorch
Italian
xlm-roberta
text classification
abusive language
hate speech
offensive language
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use MilaNLProc/hate-ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MilaNLProc/hate-ita with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="MilaNLProc/hate-ita")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("MilaNLProc/hate-ita")
    model = AutoModelForSequenceClassification.from_pretrained("MilaNLProc/hate-ita")
  • Notebooks
  • Google Colab
  • Kaggle
hate-ita
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 21 commits
dnozza's picture
dnozza
Update README.md
00a79c2 over 3 years ago
  • .gitattributes
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    Upload tokenizer.json almost 4 years ago
  • README.md
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  • config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    1.11 GB
    xet
    Upload pytorch_model.bin almost 4 years ago
  • sentencepiece.bpe.model
    5.07 MB
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    Upload sentencepiece.bpe.model almost 4 years ago
  • special_tokens_map.json
    239 Bytes
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  • tokenizer.json
    17.1 MB
    xet
    Upload tokenizer.json almost 4 years ago
  • tokenizer_config.json
    392 Bytes
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