It's unclear what tokenizer they are using and the documentation is being coy about it. It could be a more efficient or a less efficient tokenizer.
The code there implies cl100k_base has a vocab size of 100k (I guess it's in the name lol) which means it is more comprehensive than GPT-2's 50k, so fewer tokens will be necessary.
It's unclear what tokenizer they are using and the documentation is being coy about it. It could be a more efficient or a less efficient tokenizer.