Engineering PyMC3 models into production ML systems

Personally, I didn’t think that pickling and persisting the Model alongside saving the netCDF inference data, was ‘that’ big a deal. It’s certainly no different to the recommended way of persisting PyTorch models (‘models’ and weights persisted separately).

What am I missing?

I’ll consider it further and post my comments on GitHub.