The format is entirely whitebox -- the file saved is a zip archive that you can inspect. It contains the config of the model as a human-readable JSON file (a description of the architecture and hyperparameters of the model), a weights file (essentially a dict of arrays)...
The neat thing about FeatureSpace is that it's a whitebox. It's all built on top of Keras preprocessing layers, and you get direct access to them.
Want to retrieve the StringLookup layer that was used to encode a string_categorical feature? You got it.