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

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Educational tiny LLM build, perfect for AI/ML learning.

2026-04-06 AI/ML github.com
A ~9M parameter LLM that talks like a small fish. Contribute to arman-bd/guppylm development by creating an account on GitHub.
Summary

GuppyLM is an 8.7M parameter vanilla transformer trained in 5 minutes on a T4 GPU from 60K synthetic fish-themed conversations. This open-source project on GitHub provides a complete, minimal pipeline for building an LLM from scratch, emphasizing accessibility and transparency. It demonstrates that sophisticated AI systems can be understood and replicated with modest resources.

Key Takeaways
  • Clone the GuppyLM repository and run the Colab notebook to train a functional LLM from scratch in under 10 minutes, then experiment with its architecture and dataset.
Why it matters

As a senior engineer working on AI agent orchestration, grasping LLM internals through a tiny, interpretable model like GuppyLM can inform better design decisions for complex multi-agent systems and custom tooling.