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This repo accompanies the the blogpost, ["Automatically Jailbreaking Frontier Language Models with Investigator Agents"](https://transluce.org/jailbreaking-frontier-models).
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We provide a reference implementation of the dataset and reward function used in the blog post, but note that it is not optimized for efficiency or scalability. Unfortunately, we do not include the RL training loop, as it is tightly coupled with our internal research tooling. However, this codebase should serve as a useful starting point for those who want to train jailbreaking agents and reproduce our experiments.
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We provide a reference implementation of the dataset and reward function used in the blog post, but note that it is not optimized for efficiency or scalability. Unfortunately, we do not include the RL training loop, as it is tightly coupled with our internal research tooling. However, this codebase should serve as a useful starting point for those who wish to train jailbreaking agents and reproduce our experiments.
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## Dataset
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