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VigilGuard
/
vigil-llm-guard

Text Classification
Transformers
ONNX
Safetensors
English
Polish
deberta-v2
prompt-injection
security
deberta
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use VigilGuard/vigil-llm-guard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use VigilGuard/vigil-llm-guard with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="VigilGuard/vigil-llm-guard")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("VigilGuard/vigil-llm-guard")
    model = AutoModelForSequenceClassification.from_pretrained("VigilGuard/vigil-llm-guard")
  • Notebooks
  • Google Colab
  • Kaggle

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  • onnx
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • model.safetensors
    568 MB
    xet
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  • special_tokens_map.json
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  • spm.model
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  • tokenizer.json
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  • tokenizer_config.json
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