LM from First Principles is a notebook-driven guide to building and deploying language models from the ground up. Starting from a 9,025-parameter bigram that predicts one character at a time, each chapter adds one layer of capability — feedforward context, sampling strategies, self-attention, scaling — until you have a model you can push to Hugging Face. Every concept is grounded in a runnable Jupyter notebook, so you do not just read about how language models work; you watch them train, fail, improve, and generate. The book is written for practitioners who want to understand what is happening inside the model, not just call an API. You need Python and curiosity. Everything else is built from first principles.
