peremartra/Large-Language-Model-Notebooks-Course resource

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1821 stars · 448 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A free, hands-on Jupyter Notebook course on building applications with Large Language Models, covering OpenAI and Hugging Face models, LangChain, vector databases, and fine-tuning techniques like LoRA and QLoRA. It serves as the unofficial companion repository to the Apress book 'Large Language Models: Projects' and is continuously updated with new lessons and projects.

Use cases

• learn how to fine-tune large language models with LoRA and QLoRA
• build chatbots using LangChain and Hugging Face models
• understand how to use vector databases for retrieval-augmented generation
• practice prompt engineering and soft prompt tuning with notebooks
• evaluate and compare LLM performance
• learn knowledge distillation and model pruning techniques
• get hands-on projects for applying LLMs in enterprise settings

When to choose

• you want a free, practical, notebook-based introduction to working with LLMs
• you prefer learning through small projects grounded in published papers
• you want coverage of modern fine-tuning methods like PEFT, LoRA, and QLoRA
• you are reading the Apress LLM book and want updated, extended examples

When to avoid

• you need a production-ready library or framework rather than educational material
• you want a complete, polished curriculum with no ongoing changes
• you need comprehensive theory that only the companion book provides
• you require official support or a stable, versioned course syllabus

Facets

learning-resource · maturity active

machine-learning llm-training rag chatbot prompt-engineering large-language-models machine-learning artificial-intelligence tutorials python cross-platform llm-course jupyter-notebooks fine-tuning peft lora qlora langchain huggingface vector-databases knowledge-distillation llmops natural-language-processing

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