LLM-RLHF-Tuning
Discover detailed insights into LLM-RLHF-Tuning, implementing multi-stage training including instruction fine-tuning, reward model training, and PPO/DPO algorithms. The project leverages LLaMA and LLaMA2 model capabilities, endorsing efficient, distributed training with frameworks like accelerate and deepspeed. Its flexible configurations enable seamless integration of RM, SFT, Actor, and Critic models. This resource serves as a valuable guide for researchers interested in robust AI model training approaches.
