【推荐内容】合集 · jingyaogong/minimind

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MiniMind的源码解读，包含tokenizer、RoPE、MoE、KV Cache、pretraining、SFT、LoRA、DPO等完整流程 https://github.com/hans0809/MiniMind-in-Depth
🚀 让我们来从头训练一个属于自己的Mini-RWKV-7吧~ 小小的鹅也能飞得很高喔~ https://github.com/Alic-Li/Mini_RWKV_7
【DataWhale】📚 大语言模型原理与实践教程 https://github.com/datawhalechina/happy-llm
【DataWhale】📚 智能体原理与实践教程 https://github.com/datawhalechina/hello-agents
https://github.com/jingyaogong/minimind/discussions/618
https://github.com/jingyaogong/minimind/discussions/704
MiniMind文档 https://minimind.readthedocs.io https://jingyaogong.github.io/minimind
基于国产显卡华为昇腾910B复现，并且增加function calling和mcp训练数据集。 https://github.com/fzkun/minimind-ascend
从0开始训练一个大模型Minimind项目的超详细解析，包括但不限于用到的架构，算法，以及大模型面试经验 https://github.com/Tongyun1/from-minimind-to-more

一些推荐内容，欢迎追加～

Research direction: This issue is a curated list of external resources. No code changes are required. You may review the list and add additional high quality resources relevant to the MiniMind project if you have any.
Tech stack: python
Domain: machine learning
Issue type: Research
Difficulty: 1
Estimated time: Under 1 hour
Activity status: Stale
Clarity: Clear
Prerequisites: None
Newbie friendliness: 40