The TOFU dataset serves as a benchmark for evaluating unlearning performance of large language models on realistic tasks. The dataset comprises question-answer pairs based on autobiographies of 200 different authors that do not exist and are completely fictitiously generated by the GPT-4 model. The goal of the task is to unlearn a fine-tuned model on various fractions of the forget set. - Website: The landing page for TOFU - arXiv Paper: Detailed information about the TOFU dataset and its significance in unlearning tasks. - GitHub Repository: Access the source code, fine-tuning scripts, and additional resources for the TOFU dataset. - Dataset on Hugging Face: Direct link to download the…
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