Fine-Tuning 15K ChatGPT Prompts and Jailbreaks for Responsible AI

Responsible AI Interactions with GPT2 FineTunning

In the ever-evolving field of artificial intelligence, effective interaction with AI models like ChatGPT is crucial. The jailbreak_llms repository on GitHub offers a wealth of resources to enhance your understanding and prompting skills. This treasure trove contains over 15,000 ChatGPT prompts sourced from Reddit, Discord, websites, and open-source datasets, including 1,405 jailbreak prompts. Dive in to explore and enhance your prompting skills!

Overview of the Jailbreak_LLMs Repository

The jailbreak_llms repository is a goldmine of data, meticulously organized into various CSV files. This dataset serves as the largest collection of in-the-wild jailbreak prompts, making it an invaluable resource for researchers and developers interested in understanding and improving AI interactions. Here's a snapshot of what you can find:

Key Datasets

• Regular and Jailbreak Prompts
• Forbidden Question Set

Explore Diverse Prompt Scenarios

Regular Prompts

These standard prompts come from a wide array of sources, providing a comprehensive view of user interactions with ChatGPT. These prompts help in understanding how different user communities interact with AI and the kind of queries they generate. Regular prompts are essential for grasping the baseline interactions and expectations users have from AI models.

Jailbreak Prompts

Jailbreak prompts are particularly interesting as they illustrate attempts to bypass ChatGPT's safeguards. Studies have shown that these prompts can exploit weaknesses in AI models, revealing vulnerabilities that need addressing to improve AI robustness and security (Bender et al., 2021; Solaiman et al., 2019). Understanding these prompts is crucial for developing more secure and resilient AI systems.

Forbidden Question Set

This dataset includes 390 questions across 13 scenarios, adhering to OpenAI's usage policies. These questions range from illegal activities to privacy violations and health consultations. Understanding these forbidden questions is crucial for developing AI that can effectively handle and filter out inappropriate content (OpenAI, 2021). This ensures that AI systems operate within ethical and legal boundaries.

Discover Extended Forbidden Questions

For a more detailed analysis, the extended forbidden question set (forbidden_question_set_with_prompts.csv.zip) includes 107,250 samples categorized by community and prompt type. This extended dataset allows for a deeper exploration into how communities interact with forbidden content and how these interactions evolve over time.

Responsible AI Interactions with GPT-2 Fine-Tuning: A Case Study

Our GPT-Based Prompting Tool integrates seamlessly with the jailbreak_llms dataset to provide enhanced AI interaction capabilities. By fine-tuning a GPT-2 model with this specific dataset, our tool improves the relevance and context-awareness of responses generated by the AI.

Here’s how our tool leverages the jailbreak_llms repository:

1. Fine-tuning for Specific Prompts: The tool fine-tunes GPT-2 using the combined dataset of regular and jailbreak prompts, making it adept at handling both standard interactions and identifying potential jailbreak attempts.
2. Customizable API: The Flask web application we’ve developed allows users to query the model and retrieve sample prompts via API endpoints. This makes it easy to integrate our tool into various applications.
3. Improved Prompt Effectiveness: By using our tool, users can generate more accurate and contextually appropriate responses, enhancing the overall AI interaction experience.
4. Ethical AI Usage: Our tool incorporates the forbidden question set to ensure that AI responses adhere to ethical guidelines and do not engage in inappropriate content.

Conclusion

The jailbreak_llms repository is an invaluable resource for AI and NLP enthusiasts. By integrating this dataset with our GPT-Based Prompting Tool, you can enhance your understanding, improve prompt effectiveness, and ensure ethical AI usage. Explore the repository and elevate your AI interactions today!

References

1. GitHub Repository: jailbreak_llms
2. OpenAI Usage Policy: OpenAI Usage Policy
3. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ??. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610-623).
4. Solaiman, I., Brundage, M., Clark, J., & Askell, A. (2019). Release Strategies and the Social Impacts of Language Models. arXiv preprint arXiv:1909.05858.