Introduction to Reinforcement Learning from Human Feedback in Jupyter Notebooks
By
ash_at_hny
10mo ago· 3 min readenCode
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Summary
This article introduces a reference implementation for Reinforcement Learning from Human Feedback (RLHF) in Jupyter notebooks, focusing on aligning large language models to better meet users' intents through reinforcement learning.
Key quotes
· 2 pulledRLHF is a method for aligning large language models (LLMs), like GPT-3 or GPT-2, to better meet users' intents.
It is essentially a reinforcement learning approach, where rather than directly getting the reward or feedback from some environment or human, it instead trains a reward model that learns to mimic that reward.
RLHF (Supervised fine-tuning, reward model, and PPO) step-by-step in 3 Jupyter notebooks - ash80/RLHF_in_notebooks
