Visual Guide to Building a GPT from Scratch with Python: Understanding Karpathy's 200-Line Implementation
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growingswe
3mo ago· 9 min readen
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Summary
This article provides a beginner-friendly, visual walkthrough of Andrej Karpathy's 200-line Python script that implements a GPT model from scratch without any external libraries. The tutorial explains how the model trains on a dataset of 32,000 human names, covering tokenization, softmax probabilities, backpropagation, attention mechanisms, and how the tiny model learns to generate plausible names. The content is designed to make complex machine learning concepts accessible through interactive visualization and step-by-step explanation.
Key quotes
· 5 pulledAndrej Karpathy wrote a 200-line Python script that trains and runs a GPT from scratch, with no libraries or dependencies, just pure Python.
The script contains the algorithm that powers LLMs like ChatGPT.
The model trains on 32,000 human names, one per line: emma, olivia, ava, isabella, sophia... Each name is a document.
The model's job is to learn to generate plausible names.
Let's walk through it piece by piece and watch each part work.
Walk through Karpathy's 200-line GPT from scratch. Tokenize names into integers, watch softmax convert scores to probabilities, step through backpropagation on a computation graph, explore attention heatmaps, and see a tiny model learn to generate plausib
