LLM-RL-Visualized
Provides over 100 diagrams illustrating LLM and RL algorithms
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
LLM-RL-Visualized offers over 100 diagrams for understanding LLM, RL algorithms, and training methods including SFT, DPO and optimization techniques.
Good fit when
- When detailed visual explanations of LLM and RL algorithms are needed
- For studying fine-tuning techniques like DPO with specific visual aids
Avoid when
- If looking for executable code or tools rather than diagrams and visual explanations alone
- For datasets or large-scale experimental setups that require more interactive coding environments
Observed Jul 15, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Active (9d since push)
- As of Sep 7, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 7, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install LLM-RL-Visualized PyPISimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A repository containing diagrams that explain the principles of Large Language Models (LLM), Vision-Language Models (VLM), reinforcement learning (RL) algorithms, and training methods. It offers insights into SFT fine-tuning techniques, DPO direct preference optimization, and optimization technologies.
Capability facts
- Languages
- python
Source: github.language · Sep 7, 2026
Categories
Tags
README
<p align="center" <img src="src/assets/banner/幻灯片2.SVG" alt="图解大模型算法:LLM / RL / VLM 核心技术图谱" / </p <p align="center" <a href="./src/README EN.md" <img alt="English Version" src="https://img.shields.io/badge/English Version blue?style=for the badge" height="45" / </a <...
For agents
This page has a .md twin and JSON over the API.