The estimates will be in the log space, not the original dimensions. Would that difference account for the unexpected results? Also, these results were not intended to be the best estimates but serve only as the initial values for the parameters before fitting the data with the Nonlinear platform. You must back-transform the starting values with Exp() function.
I don't know about I/O error. Is it possible that the script file is locked?
I suggest making your custom model manually / interactively first. That is, define the model first as a column formula. This way will demonstrate that such a model is feasible. The Model Library is only one way to fit a custom model. It is not required. This way will also provide the correct expression if you decide later to include it in the Model Library.