Source: https://github.com/manogyasingh/transformer-visualisation Was taking a course on reasoning LMs with a 50% project component. Shortly after I started, I realised I didn't fully understand how these work. I know the architecture and the theory and steps but still there are stages where either the purpose, or the functioning was unclear to me and so I wanted an interactive walkthrough of one token's generation. So here it is, made with Opus 5.5.

It's a step by step walkthrough of a toy GPT-2 like model. Every matrix fits on screen, every number is computed live in the browser, and hovering over any cell shows the exact math of that step. It covers inference -- following the generation of one token from tokensiation to sampling, one training step of pretraining, and one PPO iteration of RLHF for post-training.

Inspired in part by Brendan Bycroft's LLM visualization (https://bbycroft.net/llm)