Email the Author
You can use this page to email Daniel Voigt Godoy about The Ultimate Guide to Fine-Tuning Large Language Models with PyTorch and HuggingFace.
About the Book
This book is a practical guide to fine-tuning Large Language Models (LLMs), offering both a high-level overview and detailed instructions on how to train these models for specific tasks. It covers essential topics, from loading quantized models and setting up LoRA adapters to properly formatting datasets and selecting the right training arguments. The book focuses on the key details and "knobs" you need to adjust to effectively handle LLM fine-tuning. Additionally, it provides a comprehensive overview of the tools you'll need along the way, including HuggingFace's Transformers, Datasets, and PEFT packages, as well as BitsAndBytes, Llama.cpp, and Ollama. The final chapter includes troubleshooting tips for common error messages and exceptions that may arise.
About the Author
Daniel has been teaching machine learning and distributed computing technologies at Data Science Retreat, the longest-running Berlin-based bootcamp, for more than three years, helping more than 150 students advance their careers.
He writes regularly for Towards Data Science. His blog post "Understanding PyTorch with an example: a step-by-step tutorial" reached more than 220,000 views since it was published.
The positive feedback from the readers resulted in an invitation to speak at the Open Data Science Conference (ODSC) Europe in 2019. It also motivated him to write the book "Deep Learning with PyTorch Step-by-Step", which covers a broader range of topics.
Daniel is also the main contributor of two python packages: HandySpark and DeepReplay.
His professional background includes 20 years of experience working for companies in several industries: banking, government, fintech, retail and mobility.