What You'll Build Four files that together make the project complete: Model.cs - the GptModel class that holds all parameters and implements the full forward pass (replacing the simplified Forward function from Chapters 6-7) AdamOptimiser.cs - a reusable class wrapping the Adam state and update from Chapter 7 FullTraining.cs - the real training loop that uses GptModel across 10,000 steps Program.cs - the finalised dispatcher with the full case wired up Depends On All previous chapters. The GptModel Class A few design notes before the code. The Forward method takes a single token at a time, not the whole sequence at once. The KV cache (passed in as parameters) holds the context from previous positions. This is the same one-token-at-a-time approach from Chapter 9: we process tokens sequentially during both training and inference. Each document or sample needs its own fresh KV cache. The model provides CreateKvCache() for that, and the caller passes it back into every Forward call for that sequence.…