Andrej Karpathy Shares 'microgpt' GitHub Gist for Minimal GPT Training

Andrej Karpathy, a founding member of OpenAI and former Director of AI at Tesla, has released a minimalist educational tool called 'microgpt' via a GitHub Gist. The resource, published on April 20, 2026, provides what Karpathy describes as 'the most atomic way to train and run inference for a GPT in pure, dependency-free Python.' It condenses the complete transformer-based Generative Pre-trained Transformer algorithm into roughly 300 lines of code, deliberately avoiding external libraries to expose the fundamental mathematical and architectural principles.

This release is strategically aimed at developers and students seeking to demystify large language models. By removing the abstraction layers of frameworks like PyTorch, the gist makes core concepts—such as token embedding, multi-head attention, and positional encoding—transparent and hackable. Karpathy, known for his popular 'Neural Networks: Zero to Hero' course, continues his mission of making AI fundamentals accessible. The code serves as both a learning scaffold and a starting point for custom, lightweight model experimentation, bypassing the complexity of billion-parameter systems like GPT-4 or Llama 3.