Collaborative Filtering - Go on training with new data

I’m currently working on a Recommender System using Collaborative Filtering and the MovieLens dataset. The goal is to export a trained collab_learner to later import and use it in an application so that you can later also upload your own movie-data as a CSV, retrain the model and get your recommendations:

I’m exporting the learner with learner.export(export.pkl) after training it for a longer time and now import the trained model in a seperate application with learner = load_learner(path=learn.path). I would now like to add a new user with its specific ratings to the model and retrain it for a few epochs. shows that the data is empty, but tells that the user and item names are there. Is it possible to attach the new data here and retrain? Or would I still need the original data in a seperate file?

Of course it works when I add the new data to the old beforehand and train a new learner from scratch, but that takes too much time for an actual application.

The used Fast AI version is 1.0.50.post1