The specific values on your scale (i.e., 0 through 10 values) are irrelevant; only their order matters. The various ordered models with their myriad of names only focus on the order and discard the specific scale values. (The specific values are only really relevant when data has been rounded or categorized, neither of which has occurred in your case.)
Other than ensuring that you have a few observations in each of your groups I would not worry too much about the proportion of observations in each group (I can't think of any statistical justification and pretty much no real-world data set would meet such a requirement anyway).
One other thing to keep in mind is that you will get a bit more statistical power if you estimate the model using all 11 data points and apply the Net Promoter Score coding only at the time of prediction (however, if doing this, you would want to check that the parameter estimates for the independent variables are approximately the same either way).