Text Classification
Transformers
Safetensors
deberta-v2
jailbreak-detection
prompt-injection
content-safety
nlp
sequence-classification
text-embeddings-inference
Instructions to use pmking27/jailbreak-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pmking27/jailbreak-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pmking27/jailbreak-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pmking27/jailbreak-detection") model = AutoModelForSequenceClassification.from_pretrained("pmking27/jailbreak-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19313a364ce00305fe595a94f45b09341a566ebc0488c10cd3f1f156e4c3953b
- Size of remote file:
- 16.3 MB
- SHA256:
- b62eef09f53b32da7928f88221ed3fd3c5b1364cee7d0e7ee5ec1bf492b9a63d
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