What it does
Core capabilities at a glance
- Cs336
- Datawhale
- GPU Programming
- Grpo
- NLP
- RL
- Scaling Laws
- SFT
Deep dive
The full breakdown - performance, comparisons, and setup
diy-llmLink to this section
diy-llm is a fine-tuning toolkit - Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer、MoE、分布式训练、缩放定律、推理与对齐，6 项渐进代码作业，掌握 LLM 全栈知识.
OverviewLink to this section
diy-llm is open-source, written primarily in Jupyter Notebook, with 2,795 GitHub stars under the Open Source license. The latest release is V0.2 (2026-08-17).
Key capabilitiesLink to this section
From the project's documentation:
- Python 编程：熟练掌握 Python 和软件工程能力
- GPU 编程（可选）：了解 CUDA 基础概念会更佳，不懂也没关系，本项目也有入门教程
- 原版课程主页：Stanford CS336 (Spring 2026)
- 感谢@jiangyinhe参与第 16 章扩展内容《LLM 的未来 - Lecun》的整理；基于中文版内容实现了第一章、前言的英文版翻译；
- 感谢@Excelius-Wang 补充 C-EVAL 中文 benchmark 的介绍，并接入到 assignment6 中
- 感谢 Stanford CS336 课程团队提供优秀的原版课程
How it fits a local-AI stackLink to this section
diy-llm runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related fine-tuning toolkits in the directory:
SourcesLink to this section
- Source code & docs: datawhalechina/diy-llm
- Official website: https://datawhalechina.github.io/diy-llm/
Stats from GitHub, 2026-11-05.
Frequently asked
Quick answers to common questions
What is diy-llm?
diy-llm is a fine-tuning tool for local AI workloads. Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack…
Is diy-llm free and open source?
Yes, diy-llm has 2,795 GitHub stars and is licensed under Open Source. You can self-host it for free on docker.
What platforms does diy-llm support?
diy-llm runs on docker.
What hardware do I need for diy-llm?
The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. diy-llm has 2,795 GitHub stars and an active community.
Does diy-llm support GPU acceleration?
diy-llm's GPU support depends on your specific setup. Check the documentation for details. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.
What are the best alternatives to diy-llm?
Popular alternatives include other fine-tuning tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.
How much does diy-llm cost?
diy-llm is free-open-source. It is completely free and open source to self-host.
Pairs well with
Complementary tools, models, and hardware