datawhalechina / diy-llm

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

weiruihhh / cs336_note_and_hw

记录我在cs336学习时的笔记和作业

ShaneLiu04 / Stanford-CS336

面向面试的Stanford CS336: Language Modeling from Scratch

lvsir18 / CS336Spring-2026-Learning-Notes

针对斯坦福大学2026 春季学期CS336课程整理的学习笔记

michaelc-yu / cs336-llm-systems

Large language model systems implementation and optimization: Transformers, BPE tokenization, FlashAttention, Triton, distributed training, GPU profiling, and GRPO reasoning RL