Building a Transformer Block: From Attention to Complete GPT
Build a complete decoder-only transformer from scratch — RMSNorm, SwiGLU, residual connections, and the full GPT architecture. Working PyTorch code included.
Category Transformer Architecture
Deep dives into transformer components: attention, positional encoding, MoE, and more.
Self-Attention from Scratch: The Core of Every LLM
Build scaled dot-product attention, multi-head attention, causal masking, KV cache, and grouped query attention from scratch in PyTorch. The fundamental operation behind GPT-4, LLaMA 3, and every modern language model.