Hi @Gi_T
After training the model with create() method you can do:
serving_model = model.create_serving_model()

print(f'Model\'s input shape and type: {serving_model.inputs}')
print(f'Model\'s output shape and type: {serving_model.outputs}')

and then save it to saved model format as always:
saved_model_path = './object_model_maker'
serving_model.save(saved_model_path, include_optimizer=False)

Check a workflow here with an audio classification example (it is still an ongoing project).