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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 Hacker News (100+)
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 Takeaway

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.