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I built GPT from scratch to understand how it works

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If you’ve ever been curious about how GPT actually works under the hood, I built a small project you might find interesting. I implemented a GPT-style transformer from scratch in a single notebook—covering tokenization, embeddings, causal self-attention, training, and autoregressive text generation without relying on high-level abstractions. The focus was on mechanistic clarity rather than scale or performance, and the notebook is structured to read more like a technical walkthrough than an experiment log. Feedback from people who’ve built or studied transformers would be very welcome.

HN · launched Jan 14, 2026 · 7 upvotes (top 65%) · 0 views

Niche: gpu infrastructure and developer tools · 129 launches, 7 in the last 7 days ▼ -30% · Explore this niche →

Category and tags

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

Visit website ↗ Source listing ↗

Could you build this?

Yes The author built an educational nanoGPT-style transformer in a single Python notebook using PyTorch. Implementing basic causal self-attention, tokenization, and forward passes is a well-trodden tutorial path that AI assistants can generate comprehensively.

Discussion

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Competitors

Other products that read as similar to this one : 159 launches clear the similarity bar, closest 8 shown.

Attention rank: #101 of 160 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 76 days after the earliest competitor.

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