license: mit
task_categories:
- question-answering
- text-generation
language: - en
pretty_name: R1-1776 Jailbreaking Examples
size_categories: - n<1K
R1-1776 Jailbreaking Examples
The R1-1776 Jailbreaking Examples dataset comprises instances where attempts were made to bypass the safety mechanisms of the R1-1776 model—a version of DeepSeek-R1 fine-tuned by Perplexity AI to eliminate specific censorship while maintaining robust reasoning capabilities. This dataset serves as a resource for analyzing vulnerabilities in language models and developing strategies to enhance their safety and reliability.
Dataset Summary
Jailbreaking R1 1776 is a blog to explain how to jailbreak post-training models that reduce overly restrictive responses.
forbidden_prompt: Malicious prompts were merged with safe example prompts provided by the DeepSeek R1 1776 blog, such as inquiries about historical events like Tiananmen Square. Since many LLMs refuse to handle harmful prompts directly, we utilized mistralai/Mistral-Nemo-Instruct-2407, known for a higher acceptance rate of controversial prompts, to generate coherent combined questions.
jailbroken_prompt: We employed the pap_misrepresentation technique, disguising harmful requests within innocent-seeming contexts, such as fictional storytelling or academic inquiry. For instance, instead of directly asking how to create a bomb, we posed a narrative scenario about a fictional character constructing one.
response: The response generated from R1-1776.