Show HN: I built a tiny LLM to demystify how language models work

Hacker News / 4/6/2026

💬 OpinionTools & Practical UsageModels & Research

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Key Points

The author describes building a small (~9M parameter) transformer-based LLM from scratch using about 130 lines of PyTorch, trained on ~60K synthetic conversation examples.
They report the model can be trained in roughly 5 minutes on free Google Colab hardware (T4), making the experiment practical for learning.
The project is positioned as a way to demystify how language models work by letting users fork the code and modify the model’s “personality.”
Community discussion on Show HN focuses on implementation details and how to adapt the approach for other characters or learning goals.

Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food.

Fork it and swap the personality for your own character.

Comments URL: https://news.ycombinator.com/item?id=47655408

Points: 227

# Comments: 17