labmlai/annotated_deep_learning_paper_implementations ? reverse-engineered prompt

Build me a Python project that teaches deep learning by example, with clear working implementations of popular papers and simple notes beside the code. I want it to feel like a living library of tutorials for things like transformers, attention, diffusion models, GANs, reinforcement learning, optimizers, normalization layers, and a few other common architectures.

The main goal is that someone can open it and actually understand how each method works, not just copy code. Please make the examples clean, easy to run, and well organized, and include a website or docs view that shows the explanations next to the code in a readable way. It should be useful for learning and for experimenting with the models locally.

If anything is unclear, check the latest docs online and keep the examples simple and practical.