This kind of thing is pretty easy to do with a much leaner model https://docs.pytorch.org/tutorials/intermediate/char_rnn_gen...

I have no affiliation with the website, but the website is pretty neat if you are learning LLM internals. It explains: Tokenization, Embedding, Attention, Loss & Gradient, Training, Inference and comparison to "Real GPT"

Pretty nifty. Even if you are not interested in the Korean language

By "modified" this person of course means that they swapped out the list of X0,000 names from English to Korean names. That is seemingly the only change.

The attached website is a fully ai-generated "visualization" based on the original blog post with little added.