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I built a tiny LLM to demystify how language models work

Details

External ID
47655408
Source
HN
Company
—
Product
I built a tiny LLM to demystify how language models work
Website domain
github.com
Launched
April 6, 2026
Cohort
—
Upvotes
915
Upvotes percentile
0.9987146529562982
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

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.

Enrichment

Theme
ML inference and model optimization
Vertical
Horizontal
Function
—
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
tiny language model for learning how language models work
Manually corrected
False

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 — 238 launches clear the similarity bar, closest 8 shown.

Attention rank: #3 of 239 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 158 days after the earliest competitor.

Other launches for this product