Hi,
we want to use a ML scenario for a keras model.
We can train the model and store the model weights as artifact.
s_buf = io.StringIO()
model.keras_model.save_weights(s_buf)
api.send("modelBlob", s_buf.read())
However, we fail to load the weights from the artifact input when applying the model.
How would that be done in Python ?
This e.g. does not work when importing a blob from the artifact storage.
model.load_weights(modelBlob)
Please advise.