# datawhalechina/diy-llm

<https://repo.masters-masters.com/en/repos/datawhalechina/diy-llm>

[Home](https://repo.masters-masters.com/en) › [datawhalechina](https://repo.masters-masters.com/en/owners/datawhalechina) › [diy-llm](https://repo.masters-masters.com/en/repos/datawhalechina/diy-llm)

datawhalechina/diy-llm has 2,769 stars on GitHub. Its RepoMasters card: RC tier. Covers pre-training data, Tokenizer, Transformer, MoE,distributed training…

| Field | Value |
| --- | --- |
| Owner | [datawhalechina](https://repo.masters-masters.com/en/owners/datawhalechina) |
| Stars | 2,769 |
| Forks | 264 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2025 |
| Topics | gpu-programming, llm, nlp, rl, sft, transformer, datawhale, grpo, cs336, scaling-laws |
| Tier | [RC (2,000 to 4,999 ★)](https://repo.masters-masters.com/en/ranks/blockbuster) |
| View on GitHub | [datawhalechina/diy-llm](https://github.com/datawhalechina/diy-llm) |

## Repository

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

The tier for repos with 2,000 to 4,999 ★. Published odds per card pulled: 3%. Rarity: Epic.

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