The model doesn't "know" how to generate tokens any more than it knows how to stop generating tokens. The sampler simply stops pulling values when it outputs a "stop token", which is a token the same way every other token is.

That is to say, it stops when it's statistically the most likely to.

I might be out of date but my understanding was that STOP was just another token that gets predicted.