现代LLM笔记本 是 AI Skill Hub 本期精选AI工具之一。综合评分 8.0 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
现代LLM笔记本 是一款基于 Jupyter Notebook 开发的开源工具,专注于 ai、llm、jupyter 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
现代LLM笔记本 是一款基于 Jupyter Notebook 开发的开源工具,专注于 ai、llm、jupyter 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 克隆仓库 git clone https://github.com/walkinglabs/modern-llm-notebook cd modern-llm-notebook # 查看安装说明 cat README.md # 按 README 完成环境依赖安装后即可使用
# 查看帮助 modern-llm-notebook --help # 基本运行 modern-llm-notebook [options] <input> # 详细使用说明请查阅文档 # https://github.com/walkinglabs/modern-llm-notebook
# modern-llm-notebook 配置说明 # 查看配置选项 modern-llm-notebook --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量(覆盖配置文件) export MODERN_LLM_NOTEBOOK_CONFIG="/path/to/config.yml"
<p align="center"> <a href="https://walkinglabs.github.io/modern-llm-notebook/?lang=en"> <picture> <source media="(prefers-color-scheme: dark) and (max-width: 600px)" srcset="assets/brand/modern-llm-wordmark-compact-dark.svg"> <source media="(max-width: 600px)" srcset="assets/brand/modern-llm-wordmark-compact.svg"> <source media="(prefers-color-scheme: dark)" srcset="assets/brand/modern-llm-wordmark-dark.svg"> <img src="assets/brand/modern-llm-wordmark.svg" alt="Modern LLM Notebook — From scratch. Into practice." width="880"> </picture> </a> </p>
<p align="center"> <strong>Learn modern LLMs from scratch, one detailed example and experiment at a time.</strong> </p>
<p align="center"> Train a BPE tokenizer, prepare real data, and pretrain a 64M-class model. Continue with SFT, then explore MoE, tool calling, post-training, and inference. </p>
<p align="center"> <a href="README.md"><strong>English</strong></a> · <a href="README-CN.md"><strong>中文文档</strong></a> · <a href="https://walkinglabs.github.io/modern-llm-notebook/?lang=en"><strong>Read Online</strong></a> · <a href="https://colab.research.google.com/github/walkinglabs/modern-llm-notebook/blob/main/notebooks-en/part1-foundation/01-tokenizer-basics.ipynb"><strong>Start in Colab</strong></a> · <a href="https://modelscope.cn/notebook/share/github/walkinglabs/modern-llm-notebook/blob/main/notebooks-en/part1-foundation/01-tokenizer-basics.ipynb"><strong>ModelScope</strong></a> · <a href="https://developer.amd.com.cn/radeon/templates/4015/preview"><strong>AMD GPU Template</strong></a> · <a href="https://discord.gg/XU7DQmpqk"><strong>Join Discord</strong></a> </p>
<p align="center"> <a href="https://github.com/walkinglabs/modern-llm-notebook/stargazers"> <img alt="GitHub stars" src="https://img.shields.io/github/stars/walkinglabs/modern-llm-notebook?style=social"> </a> <a href="https://github.com/walkinglabs/modern-llm-notebook/actions/workflows/quality.yml"> <img alt="Quality checks" src="https://github.com/walkinglabs/modern-llm-notebook/actions/workflows/quality.yml/badge.svg"> </a> <a href="https://github.com/walkinglabs/modern-llm-notebook/blob/main/LICENSE"> <img alt="License" src="https://img.shields.io/badge/license-CC%20BY--NC--SA%204.0-blue"> </a> <img alt="Python" src="https://img.shields.io/badge/Python-3.9%2B-3776AB"> <img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-2.0%2B-EE4C2C"> <img alt="Languages" src="https://img.shields.io/badge/Languages-English%20%7C%20Chinese-2ea44f"> </p>
<p align="center"> <a href="#course-preview">Preview</a> · <a href="#what-makes-this-course-different">Approach</a> · <a href="#from-zero-to-a-trained-model">Training Path</a> · <a href="#models--benchmarks">Models & Benchmarks</a> · <a href="#data-sources-and-processing">Data Pipeline</a> · <a href="#learning-roadmap">Roadmap</a> · <a href="#curriculum">Curriculum</a> · <a href="#quick-start">Quick Start</a> · <a href="#run-online-through-partner-platforms">Partners</a> · <a href="#project-status">Status</a> · <a href="#contributing">Contributing</a> </p>
Some sandbox or CI environments prohibit opening local sockets, which can prevent the standard Jupyter kernel protocol, nbclient, and nbconvert --execute from working. The repository provides a kernel-free runner for this case. It executes code cells sequentially in Python and writes their outputs back to the English notebook files:
python scripts/execute_notebooks_en_no_kernel.py
</details>
<details> <summary>Data sources, cleaning steps, and synthesis references</summary>
高质量的LLM构建教程
该工具使用 NOASSERTION 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
经综合评估,现代LLM笔记本 在AI工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | modern-llm-notebook |
| 原始描述 | 开源AI工具:A hands-on course for building modern LLMs from scratch in PyTorch, with 23 runn。⭐15 · Jupyter Notebook |
| Topics | aillmjupyter |
| GitHub | https://github.com/walkinglabs/modern-llm-notebook |
| License | NOASSERTION |
| 语言 | Jupyter Notebook |
收录时间:2026-05-26 · 更新时间:2026-05-30 · License:NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。