Shypd.aiThe largest open index of AI toolssafe-rlhf is an open-source framework for Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback. It provides a reproducible code pipeline for alignment research, supporting SFT, RLHF, and Safe RLHF training methods.
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safe-rlhf is an open-source framework designed for research into Constrained Value Alignment using Safe Reinforcement Learning from Human Feedback (RLHF). It offers a comprehensive and reproducible code pipeline, making it an invaluable resource for alignment research. The framework supports various training methods, including Supervised Fine-Tuning (SFT), standard Reinforcement Learning from Human Feedback (RLHF), and Safe RLHF. This allows researchers to explore different approaches to aligning AI models with human values while ensuring safety constraints are met. Its modular design facilitates experimentation and integration into existing research workflows, providing a robust platform for developing and evaluating safe AI systems.
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