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neuralchemy
/
prompt-injection-deberta

Text Classification
Transformers
Safetensors
English
deberta-v2
prompt-injection
jailbreak
security
llm-security
ai-safety
deberta
deberta-v3
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use neuralchemy/prompt-injection-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use neuralchemy/prompt-injection-deberta with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="neuralchemy/prompt-injection-deberta")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("neuralchemy/prompt-injection-deberta")
    model = AutoModelForSequenceClassification.from_pretrained("neuralchemy/prompt-injection-deberta")
  • Notebooks
  • Google Colab
  • Kaggle
prompt-injection-deberta
292 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
m4vic's picture
m4vic
Add comprehensive model card with dataset tag, benchmarks, and usage examples
e271c82 verified 2 months ago
  • .gitattributes
    1.52 kB
    initial commit 2 months ago
  • README.md
    4.51 kB
    Add comprehensive model card with dataset tag, benchmarks, and usage examples 2 months ago
  • config.json
    937 Bytes
    Add fine-tuned DeBERTa-v3-small 2 months ago
  • model.safetensors
    284 MB
    xet
    Add fine-tuned DeBERTa-v3-small 2 months ago
  • tokenizer.json
    8.34 MB
    Add tokenizer 2 months ago
  • tokenizer_config.json
    509 Bytes
    Add tokenizer 2 months ago