Issue #96 LLMs Edwin Dong, Lalit Julapalli
MicroGPT, Simply Explained
Free editionPRO edition
This week’s PRO issue includes a Colab notebook that dives into the core of MicroGPT, exploring every component of the 200-line elegant LLM template, while also introducing modern attention optimizations.
As always, the code in this issue can be executed on a normal home PC and does not require a large amount of VRAM.
The monthly interview question bank can be found here. These are industry standard questions that are tested across major tech companies, AI research firms, and more. The questions are sorted by difficulty and topic. Check back frequently for more questions!
Andrej Karpathy is a well-renowned computer scientist and leader in today’s Artificial Intelligence public forum. Some of his best work stems from the craft that the community deems "minimalist engineering.”
On February 12th, he posted on his GitHub a blog called MicroGPT, where he showcases his latest creation: a 200-line project containing the very backbone of frontier model chatbots like ChatGPT.
Today, we’ll visually break down the project, piece by piece, unraveling the engineering marvel. We’ll look at the complete architecture, from the dataset to the last layer output, and understand deeply how each component contributes to the full mechanism.
MicroGPT is not meant to replace the frontier models, by no means. In fact, the model simply outputs predictions for how to complete names, which its original database is full of.
However, it represents something bolder. Even with how sophisticated modern LLMs become, the core of what makes them work can be simple.
In Karpathy’s breakdown, these principles are elegantly on full display.
This edition is for PRO members.
