ai-twinkle/rlhf-book-zh-tw

This project is a Traditional Chinese translation of the book Reinforcement Learning from Human Feedback by Nathan Lambert, maintained by the Twinkle AI Community in Taiwan. It is an unofficial community translation, though the original author is aware of it, and it covers all seventeen chapters plus three appendices of the original text. What sets this apart from a plain translation is that every chapter comes with an interactive demo you can play with directly in a browser, built to make abstract ideas from the book concrete. Examples include a simulator for the PPO clipping objective and GRPO group advantage, an explorer for the Bradley-Terry reward model, a DPO loss surface you can manipulate, a visualizer comparing forward and reverse KL divergence, and a rejection sampling and best of N simulator. There are eighteen such labs in total, one per chapter plus a few in the appendices, covering topics from the history of RLHF through instruction tuning, reward models, reinforcement learning, evaluation, and model personality. The repository is organized into a content folder holding each chapter as its own markdown file, a webapp folder containing the static, fully offline capable interactive website, and a build script that turns the markdown into the final web pages. To use it locally, you run a simple Python web server from the webapp folder and open it in a browser, and after editing any chapter file or adding a new interactive widget you rerun the build script to regenerate the site. The translation is released under the Creative Commons BY-NC-SA 4.0 license, meaning it can be shared and adapted for non-commercial purposes only, with attribution and the same license carried forward, matching the license of the original book. The README encourages readers to support the original author by buying the print edition, and it includes the citation format for referencing the source book in academic work.