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s-nlp
/
roberta_toxicity_classifier_v1

Text Classification
Transformers
PyTorch
roberta
Model card Files Files and versions
xet
Community

Instructions to use s-nlp/roberta_toxicity_classifier_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use s-nlp/roberta_toxicity_classifier_v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="s-nlp/roberta_toxicity_classifier_v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("s-nlp/roberta_toxicity_classifier_v1")
    model = AutoModelForSequenceClassification.from_pretrained("s-nlp/roberta_toxicity_classifier_v1")
  • Notebooks
  • Google Colab
  • Kaggle
roberta_toxicity_classifier_v1
502 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
cointegrated's picture
cointegrated
Create README.md
0aeddbf over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    446 Bytes
    Create README.md over 4 years ago
  • config.json
    530 Bytes
    the first commit over 4 years ago
  • merges.txt
    456 kB
    the first commit over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    501 MB
    xet
    the first commit over 4 years ago
  • special_tokens_map.json
    239 Bytes
    the first commit over 4 years ago
  • tokenizer_config.json
    25 Bytes
    the first commit over 4 years ago
  • vocab.json
    798 kB
    the first commit over 4 years ago