llm-course
mlabonne/llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
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Install
git clone https://github.com/mlabonne/llm-courseREADME
π Follow me on X β’ π€ Hugging Face β’ π» Blog β’ π LLM Engineer's Handbook
The LLM course is divided into three parts:
- 𧩠LLM Fundamentals is optional and covers fundamental knowledge about mathematics, Python, and neural networks.
- π§βπ¬ The LLM Scientist focuses on building the best possible LLMs using the latest techniques.
- π· 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, 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.
π Notebooks
A list of notebooks and articles I wrote about LLMs.
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Tools
| Notebook | Description | Notebook |
|---|---|---|
| π§ LLM AutoEval | Automatically evaluate your LLMs using RunPod | |
| π₯± LazyMergekit | Easily merge models using MergeKit in one click. | |
| π¦ LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. | |
| β‘ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. | |
| π³ Model Family Tree | Visualize the family tree of merged models. | |
| π ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. | |
| βοΈ AutoAbliteration | Automatically abliteration models with custom datasets. | |
| π§Ό AutoDedup | Automatically deduplicate datasets using the Rensa library. |
Fine-tuning
| Notebook | Description | Article | Notebook |
|---|---|---|---|
| Fine-tune Llama 3.1 with Unsloth | Ultra-efficient supervised fine-tuning in Google Colab. | Article | <a href="https://colab.research.google.c |