I built a repo for implementing and training LLM architectures from scratch in minimal PyTorch — contributions welcome! [P]

Hey everyone, I've been working on a repo where I implement large language model architectures using the simplest PyTorch code possible. No bloated frameworks, no magic abstractions - just clean, readable code that shows exactly what's happening under the hood. The mission is simple: make LLM internals approachable. If you've ever wanted to understand how these models actually work - not just use them - this is the kind of place where you can read the code and actually follow it.