⚡ Building Transformers from Scratch with PyTorch
Hand-write every component of a GPT-style decoder — tokenizer, attention, blocks, training, KV-cache generation — and train your own tiny GPT.
10-Lesson mini-course — Hand-write every component of a GPT-style decoder — tokenizer, attention, blocks, training, KV-cache generation — and train your own tiny GPT.
Like every course on this site, each lesson is a deep, code-first lesson: an intuition-first explainer, a staged code walkthrough explaining the methodology line by line, visuals, and a 🧪 Your task exercise with a hidden solution. Theory lives in the AI & ML Encyclopedia; here you build.
▶ Start Lesson 1 📚 All mini-courses
Syllabus
| # | Lesson |
|---|---|
| Lesson 1 | The Transformer Map: What We’re Building |
| Lesson 2 | Tokenization & the Data Pipeline |
| Lesson 3 | Embeddings & Positional Information |
| Lesson 4 | Scaled Dot-Product Attention from Scratch |
| Lesson 5 | Multi-Head Attention: Many Perspectives in Parallel |
| Lesson 6 | The Transformer Block: Where Everything Clicks Together |
| Lesson 7 | Assembling the Full GPT |
| Lesson 8 | Training the Tiny GPT |
| Lesson 9 | Generation & Decoding: Making Your GPT Speak |
| Lesson 10 | From Tiny-GPT to the Real Thing |