Can GraphModels be extended (add layers for example) or used in transfer learning?

[Mah_Neh]

I am testing a few models, but the SavedModels that I find (In the hub for example) and are loaded with GraphModels API does not seem to allow any customization of the Neural Net…

Is this correct ? Are SavedModels currently to use “as-is” and only LayersModel can be retrained or modified ?

[jasmine_dhantule]

Hi @Mah_Neh, thanks for posting this issue.

You can try to load the tensorflow saved model in keras using
model = keras.saving.load_model("path_to_saved_model") and then try to modify it’s architecture.

Let me know if that works for you.
Thanks!