Instructions to use GuardrailsAI/prompt-saturation-attack-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GuardrailsAI/prompt-saturation-attack-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GuardrailsAI/prompt-saturation-attack-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GuardrailsAI/prompt-saturation-attack-detector") model = AutoModelForSequenceClassification.from_pretrained("GuardrailsAI/prompt-saturation-attack-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
A small model to detect saturation jailbreak attacks. Not intended for standalone use against other kinds of jailbreaks.
Model Details
Model Description
- Developed by: Guardrails AI, Joseph Catrambone
- Funded by [optional]: Guardrails AI
- Model type: Transformer, BERT
- Language(s) (NLP): English
- License: Restrictive
- Finetuned from model [optional]: bert-tiny
Model Sources [optional]
Uses
Designed as a small prefilter for a subset of saturation attacks.
Out-of-Scope Use
Not designed to catch other types of jailbreaks. Saturation protection is one part of a more complite suite of defenses against improper use of ML systems.
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Model tree for GuardrailsAI/prompt-saturation-attack-detector
Base model
google-bert/bert-base-uncased