How to use multinomial naive bayes for both text and non text data using python?
Three are several ways to do that:

simply concatenate Hashing Vectors with integers and train on that bigger features vector. It will work.

It would be more reasonable to do so using different classifier, beacuse MultinominalNB can't model the interactions between the features. But if you want nothing else but MultinominalNB, you can do it. You can also:

train two of them - one on HV, one on integers, and weigth the output, or
use MultinominalNB on text and different classifier on integers, or
use MultinominalNB on text, and take the output as a features both with integers.
The data consists of text parameters as well as integer parameters. The problem is to train machine with both data. Hashing Vectorizer is used for text parameters training.
Thanks in advance....