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Every number in a tiny GPT, from one forward pass to one step of RLHF

llm.manogya.dev

In the maker’s words

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…
xtcntr, launching on Hacker News

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