1. Introduction
2. Project setup
3. Model configuration
4. Feed-forward network
5. Causal masking
6. Multi-head attention
7. Layer normalization
8. Transformer block
9. Stacking transformer blocks
10. Language model head
11. Encode and decode tokens
12. Text generation
13. Load weights and run model