Large Language Model Notebooks Course
A free, in-progress hands-on course of Jupyter notebooks that is the unofficial companion repository to a book on applying large language models, covering techniques, projects and enterprise-scale solutions.
Large Language Model Notebooks Course is a practical, hands-on course about large language models and their applications, delivered as Jupyter notebooks and posted incrementally as lessons are completed. It is the unofficial repository for a book on applying and implementing strategies for large language models, and its notebooks are updated with new examples and chapters beyond what the book itself contains.
The course has three sections: techniques and libraries, which covers chatbots, code generation, the OpenAI API, Hugging Face, vector databases, LangChain, fine-tuning, PEFT, soft-prompt tuning, LoRA, QLoRA, model evaluation and knowledge distillation through small worked examples; projects, which builds larger examples and discusses their design trade-offs and related LLMOps concerns; and enterprise solutions, which looks at how large language models fit into broader systems for organizations with thousands of employees.
It uses models from OpenAI and the Hugging Face library.