Tiny LLM Educational Framework

A simplified, from-scratch implementation of a small language model (~9M parameters) that trains quickly on consumer hardware, designed to teach how LLMs actually work. Users can fork and customize the character/personality.

Interest in LLM internals has grown alongside the proliferation of wrapper apps — developers who built on top of APIs are now trying to understand what's underneath, and courses like Karpathy's nanoGPT have shown real demand for hands-on, minimal implementations. No clear incumbent owns the "fork-and-train-your-own-tiny-LLM" niche specifically, though nanoGPT and Andrej Karpathy's free YouTube content are the obvious substitutes, which is the core problem. The $100–500/month revenue band requires either a small paid cohort or a course wrapper, but competing against high-quality free content makes conversion extremely difficult without a genuinely differentiated angle — the customizable personality hook alone won't do it. The most likely failure mode is that the target audience finds the free alternatives sufficient and there's no compelling reason to pay.