MicroGPT explained interactively
Hacker News
March 1, 2026
AI-Generated Deep Dive Summary
MicroGPT is a minimalist implementation of the GPT language model, created by Andrej Karpathy in just 200 lines of pure Python code with no external libraries. This project demonstrates how even a small-scale model can generate plausible text by training on a dataset of 32,000 human names. The model learns patterns in the data and produces names like "kamon" or "karai," showcasing its ability to understand character sequences and predict likely next characters. By walking through Karpathy's code, readers gain insights into the core components of large language models, such as tokenization, prediction mechanisms, and training processes.
The model begins by converting text into numerical tokens, assigning each unique character a distinct integer ID. For example, lowercase letters are assigned IDs 0-25, with an additional special token (BOS) to mark the start and end of sequences. This simple tokenization method allows the model to process text as numerical inputs. The prediction task involves sliding through the sequence of tokens one position at a time, using the current context to predict the next character. At each step, the model outputs raw scores (logits) for all possible next tokens, which are then converted into probabilities using softmax. This transformation ensures that the output values sum to 1, representing a probability distribution over possible
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Originally published on Hacker News on 3/1/2026