Hello.
I’ve also encountered this problem and I all I came across with was to write some function that can apply trained tabular model to any new dataframe (apply in batches rather than row by row).
Here is my topic about it Some useful functions for tabular models
And here is the notebook for Rosmann case https://github.com/Pak911/fastai-shared-notebooks
But there is a catch (yes there’s always one) info on normalization is not stored in the learn object, so I had two split databunch creation process in to two phases (details in the post I’ve linked)
So this way you can test your new (production?) data without adding it as a test set
Hope this will help