Building GPT from Scratch: What I Learned Implementing a Transformer in Raw PyTorch

A developer built a GPT-style language model entirely from scratch using PyTorch, trained on Shakespeare's text, to truly understand how large language models work internally. Starting with a simple bigram model, then implementing self-attention, multi-head attention, and full Transformer blocks by hand, the project produced an 11-million-parameter model that learned Shakespeare's writing style purely by predicting one character at a time, with training loss dropping from 4.28 to 1.08.