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I built a tiny LLM to demystify how language models work

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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.

HN · launched Apr 6, 2026 · 915 upvotes (top 1%) · 2 views

Niche: large language models · 191 launches, 4 in the last 7 days ▼ -33% · Explore this niche →

Category and tags

  • Education
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes The project is ~130 lines of PyTorch implementing a standard educational transformer model and training loop on a small synthetic dataset in Google Colab.

Discussion

20 comments analyzed.

Competitors mentioned: LLM from Scratch book, Toki pona translation models

Concerns raised: Unclear value proposition and how it demystifies LLMs, Generic AI chat interface without differentiation, Distillation amplifies artifacts from host model, Insufficient training samples for generating new data

Feature requests: Include codebase documentation context in explanations, Clarify design decisions and abstractions in documentation

Competitors

Other products that read as similar to this one : 525 launches clear the similarity bar, closest 8 shown.

Attention rank: #3 of 526 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 158 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.