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fgaim
/
tiroberta-abusiveness-detection

Text Classification
Transformers
Safetensors
Tigrinya
roberta
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use fgaim/tiroberta-abusiveness-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use fgaim/tiroberta-abusiveness-detection with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="fgaim/tiroberta-abusiveness-detection")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("fgaim/tiroberta-abusiveness-detection")
    model = AutoModelForSequenceClassification.from_pretrained("fgaim/tiroberta-abusiveness-detection")
  • Notebooks
  • Google Colab
  • Kaggle
tiroberta-abusiveness-detection
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  • 2 contributors
History: 2 commits
fgaim's picture
fgaim
Add trained model binary and model card
baa3af3 12 months ago
  • .gitattributes
    1.48 kB
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  • README.md
    4.39 kB
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  • clean_clean_predictions_test.json
    49.7 kB
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  • clean_text_predictions_test.json
    49.7 kB
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  • config.json
    859 Bytes
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  • merges.txt
    1.23 MB
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  • model.safetensors
    499 MB
    xet
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  • predictions_test.json
    49.7 kB
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  • special_tokens_map.json
    965 Bytes
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  • text_clean_predictions_test.json
    49.7 kB
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  • text_text_predictions_test.json
    49.7 kB
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  • tokenizer.json
    5.11 MB
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  • tokenizer_config.json
    1.28 kB
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  • training_args.json
    4.05 kB
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  • vocab.json
    1.58 MB
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