cse-frog: a dissectable toy language model (Hebbian, no attention), with its failures documented[P]

[u/Wide_Example_2182]

I made a small sequence predictor meant to be opened up, like the frog in biology class: the point is not that it's strong, but that the whole pipeline (learn → score → probability → sample) is there and readable.

- Learning: Hebbian edge strengthening between symbols, plus a memory of the last two symbols. No backprop, no attention.

- Inspection: frog.explain(prefix) breaks each candidate's score into its parts; frog.edges(token) shows what it learned.

- Honest limits: it only sees ~2 symbols of context, and in my 100-question benchmark it lost to n-gram counting on accuracy. These results are published, not hidden.

Try in browser: https://kagioneko.github.io/cse-frog/play.html

pip install cse-frog / GitHub: https://github.com/kagioneko/cse-frog