LLM RL Environments Lil Course A little course on Reinforcement Learning Environments for evaluating and training Language Models. Unlike classic fine-tuning, RL environments let models explore and improve beyond what curated datasets can teach. In this course, we'll build a Tic Tac Toe environment and use it to transform a Small Language Model () into a master player that beats . ➡️ Start here: Chapter 1 - Agents, Environments, and LLMs 🎥 Video walkthrough @ AI Engineer 🤗🕹️ Play against Mr.
| Stars | 201 |
| Forks | 16 |
| Language | Python |
| Category | LLM 插件 |
| License | Apache-2.0 |
| Quality Score | 36.16/100 |
| Last Updated | 2026-05-27 |
| Created | 2026-01-18 |
| Platforms | python |
| Est. Tokens | ~1994k |
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llm-rl-environments-lil-course is 🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models. It is categorized as a LLM 插件 with 201 GitHub stars.
llm-rl-environments-lil-course is primarily written in Python. It covers topics such as course, grpo, language-models.
You can find installation instructions and usage details in the llm-rl-environments-lil-course GitHub repository at github.com/anakin87/llm-rl-environments-lil-course. The project has 201 stars and 16 forks, indicating an active community.
llm-rl-environments-lil-course is released under the Apache-2.0 license, making it free to use and modify according to the license terms.