1. Introduction
2. Setup
3. Model configuration
4. Causal masking
5. Layer normalization
6. Feed-forward network
7. Token embeddings
8. Position embeddings
9. Multi-head attention
10. Residual connections and layer normalization
11. Transformer block
12. Stacking transformer blocks
13. Language model head
14. Text generation