It’s a design choice and is similar to the number of hidden neurons in a linear layer.
Using more kernels gives the model more capacity, which might be helpful or harmful depending on the problem. In the tutorial it might just have been a decision to make the model performing good enough, while still having enough speed so that it can run on CPU smoothly.