Naive Bayes implementation: why Laplace smoothing is different from theory?
I think the answer is just that in the case of the Bernoulli model, your variables are binary variables which means the only values they can take are 0 or 1. Therefore the "number of features" also called "size of the vocabulary" in the case of text classification is limited to 2.