--- title: "llm-course" type: "tool" slug: "mlabonne-llm-course" canonical_url: "https://www.graphcanon.com/tools/mlabonne-llm-course" github_url: "https://github.com/mlabonne/llm-course" homepage_url: "https://mlabonne.github.io/blog/" stars: 80726 forks: 9408 primary_language: null license: "Apache-2.0" categories: ["llm-frameworks", "developer-tools"] tags: ["llm", "machine-learning", "course", "large-language-models", "roadmap"] updated_at: "2026-07-07T18:58:38.680775+00:00" --- # llm-course > Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. This repository features a course on LLMs, divided into foundational knowledge, scientific development of models, and engineering applications. It includes interactive Colab notebooks for practical learning and deployment of LLM technologies. ## Facts - Repository: https://github.com/mlabonne/llm-course - Homepage: https://mlabonne.github.io/blog/ - Stars: 80,726 · Forks: 9,408 · Open issues: 84 · Watchers: 750 - License: Apache-2.0 - Last pushed: 2026-02-05T13:09:26+00:00 ## Categories - [LLM Frameworks](/categories/llm-frameworks.md) - [Developer Tools](/categories/developer-tools.md) ## Tags llm, machine-learning, course, large-language-models, roadmap ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,347) - [JavaGuide](/tools/snailclimb-javaguide.md) - Snailclimb/JavaGuide: 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发 (★ 156,863) - [open-webui](/tools/open-webui-open-webui.md) - User-friendly AI Interface (Supports Ollama, OpenAI API, ...) (★ 144,575) - [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) - 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. (★ 116,702) ## README (excerpt) ```text
LLM Course

𝕏 Follow me on X • 🤗 Hugging Face • 💻 Blog • 📙 LLM Engineer's Handbook


LLM Engineer's Handbook CoverThe LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** is optional and covers fundamental knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. > [!NOTE] > Based on this course, I co-wrote the [LLM Engineer's Handbook](https://packt.link/a/9781836200079), a hands-on book that covers an end-to-end LLM application from design to deployment. The LLM course will always stay free, but you can support my work by purchasing this book. For a more comprehensive version of this course, check out the [DeepWiki](https://deepwiki.com/mlabonne/llm-course/). ## 📝 Notebooks A list of notebooks and articles I wrote about LLMs.
Toggle section (optional) ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 [LLM AutoEval](https://github.com/mlabonne/llm-autoeval) | Automatically evaluate your LLMs using RunPod | Open In Colab | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. | Open In Colab | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. | Open In Colab | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. | Open In Colab | | 🌳 Model Family Tree | Visualize the family tree of merged models. | Open In Colab | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. | Open In Colab | | ✂️ AutoAbliteration | Automatically abliteration models with custom datasets. | Open In Colab | | 🧼 AutoDedup | Automatically deduplicate datasets using the Rensa library. | Open In Colab | ### Fine-tuning | Notebook | Description | Article | Notebook | |---------------------------------------|-------------------------------------------------------------------------|---------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------| | Fine-tune Llama 3.1 with Unsloth | Ultra-efficient supervised fine-tuning in Google Colab. | [Article](https://mlabonne.github.io/blog/posts/2024-07-29_Finetune_Llama31.html) |