This document lists all the valuable resources referenced throughout the project. It’s intended to serve as a curated knowledge base to help contributors understand and dive deeper into each concept behind LLM development.
-
Build a Large Language Model (From Scratch) – Sebastian Raschka
https://www.manning.com/books/build-a-large-language-model-from-scratch -
The Deep Learning Book – Ian Goodfellow, Yoshua Bengio, Aaron Courville
https://www.deeplearningbook.org/ -
Natural Language Processing with Transformers – Lewis Tunstall, Leandro von Werra, Thomas Wolf
https://transformersbook.com/
- Attention Is All You Need (Vaswani et al., 2017)
- GPT: Improving Language Understanding by Generative Pre-Training (Radford et al., 2018)
- PyTorch Documentation
- Hugging Face Transformers Docs
- Hugging Face Datasets
- Gradio for LLM Demos
- Hugging Face Course (Free)
- Build LLMs from Scratch – YouTube Playlist (by Raschka)
- Build LLMs from Scratch – YouTube Playlist (by Vizuara)
- Transformer – YouTube Playlist (by Campusx)
- Stanford CS224n: NLP with Deep Learning
- FastAI NLP Course
- The Illustrated Transformer (Jay Alammar)
- How GPT Works (by Stephen Wolfram)
- Sebastian Raschka’s blog
Feel free to contribute more resources via pull requests!