Generally a model testing program is telling you which model fits best to the data not specifying what the parameter values should be. So you should probably let the alpha (gamma shape parameter) and pInv parameters just be sampled with the rest of your parameters.
The category count is not a parameter of the model but simply how many discrete categories of rate the model uses to approximate the continuous gamma distribution. The more categories you use the better the approximation is but the slower BEAST will take to run. The thing to realise is that we don’t need this to be a good approximation as we don’t believe it is really gamma distributed. Most people use a value of 4-8 for this. Probably the best thing is to use the same as J-Model test.
Andrew