Understanding RL for model training, and future directions with GRAPE
6 hours ago
- #Instruction Tuning
- #Model Training
- #Reinforcement Learning
- Provides a self-contained exposition of key algorithms for instruction tuning of models.
- Discusses and develops methods step by step using simplified and explicit notation focused on LLMs.
- Aims to eliminate ambiguity and provide a clear and intuitive understanding of the concepts.
- Minimizes detours into broader RL literature and connects concepts to LLMs.
- Includes a literature review of new techniques and approaches beyond those detailed.
- Presents new ideas for research and exploration in the form of GRAPE (Generalized Relative Advantage Policy Evolution).