Practical overview
When it fits
Use it as a guided notebook-based learning resource when you want to study LLM techniques and follow small projects before developing larger applications.
Who it is for
- Engineers, researchers and developers learning to apply large language models.
- Readers who prefer following code examples alongside explanatory articles.
Documented uses
- Study examples of chatbot and code-generation projects.
- Explore LLM techniques including fine-tuning, model evaluation and knowledge distillation.
- Learn how vector databases and LLM libraries fit into larger projects.
- Compare design choices across project implementations.
Requirements & limits
The GitHub repository is public and MIT-licensed. Most notebooks are hosted on Colab and a few on Kaggle; some require more memory than Colab’s free tier, for which the course suggests a local environment or Colab Pro.
- The repository is an unofficial companion to a book and does not contain all of the book’s information.
- The course is described as in ongoing development, with lessons and samples added as they are completed.
- Notebooks are distributed across Colab and Kaggle, and some have memory requirements beyond Colab’s free tier.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Follow a course lesson using its notebook and article
Work through a lesson in the LLM course by pairing its notebook with the accompanying explanation.
Before you start
- Access to a lesson page and its linked notebook and article.
- A Colab or Kaggle account if using notebooks hosted on those services, or an environment for running notebooks locally.
Steps
Choose a course section and lesson; open the lesson page linked from its title.
Open the lesson’s notebook and its accompanying article.
Keep the article open alongside the notebook and follow the explanation while working through the notebook.
If the notebook requires more memory than free Colab provides, use your own environment or Colab Pro.
Expected outcome
A guided, notebook-based lesson using the course’s code and explanations.
Guide limitations
- The GitHub course does not contain all the information in the accompanying book.
- Most notebooks are hosted on Colab, with some on Kaggle.
- Some notebooks need more memory than the free version of Colab provides.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 14 October 2026
- Original website title
- peremartra/Large-Language-Model-Notebooks-Course · Official homepage title · retained in its source language