prompt-injection-defense

Introduction to Prompt Injection Defense

The wagner-group/prompt-injection-defense repository focuses on fine-tuning base models to build robust task-specific models, specifically targeting prompt injection vulnerabilities. This project provides the necessary framework and tools to enhance the reliability of AI models in interpreting prompts and generating outputs accurately.

Key Features

• Functionality: Implements two main functions: jatmo for running frameworks with datasets and jatmo_synthetic for generating datasets.
• Parallel Requests: Ability to run servers for making parallel requests, improving efficiency in generating outcomes.
• Versatile Usage: Support for one-shot examples and multiple examples in generating datasets, enhancing flexibility.
• Integration: Seamlessly integrates with OpenAI models, offering a structured way to improve model responses based on prompts.

Benefits

• Robustness: Creates strong defenses against prompt injection attacks.
• Customizability: Users can tailor models to specific tasks, ensuring high relevance and accuracy.
• Ease of Use: Simple setup instructions make it accessible for both developers and researchers interested in enhancing AI performance.

Highlights

• The project has garnered attention with contributions from different developers, indicating a collaborative effort towards AI safety.