To download a model, click the Experiments option menu ( ) and select Download. This will download the trained model with weights from the epoch with the best validation loss as a .h5-file for deployment in Keras-based python programs.
Currently, Keras v2.1.6-tf compatible .h5 file is provided for running a forward pass. Make sure to set compile=False when loading the model in Keras. If import Keras doesn’t work, try from Tensorflow import keras instead.
An example of how you can load a .h5-model is explained in the Keras documentation.
This solution does currently not take pre/post processing into account which means that any normalization or categorical preprocessing will not be part of this model. Currently, these operations and the metadata used to apply them is not exposed.
Therefore we recommend for users that rely on deploying .h5-files from their platform in their own systems to do all pre-processing such as normalization and one-hot preprocessing outside the platform.