In deep learning what is the difference between Weights Size and Model Size?

Question

In deep learning, what is the difference between Weights Size and Model Size? (often expressed in MB)

Answer 1

Number of weights is a number of tunable parameters in your model. Each of them can be represented as various numerical formats, e.g. 8, 16 or 32 bit ones. Model size is rougly the multiplication of the two above, but there are some other things can can be considered part of the model size, e.g. connectivity information, architecture, extra logis that needs to be stored to be able to define the model.