How to save a fitted sts model?

I followed the example https://github.com/tensorflow/probability/blob/master/tensorflow_probability/examples/jupyter_notebooks/Structural_Time_Series_Modeling_Case_Studies_Atmospheric_CO2_and_Electricity_Demand.ipynb to build and fit a sts model for time series prediction which is easy and works pretty well as long as one sticks to the tutorial.

What i do not understand is, how to save a model which is fitted on some training data like it is done with neural networks in tensorflow or high lvl apis like keras.

The stretched out model fitting, elbo loss minimizing and prediction process makes it hard to understand where the model parameters lie that have been optimized.

Finally I would like to know if / how it is possible to continue training an previously fitted sts model for time-series prediction on new data.

Start with the linked Structural_Time_Series_Modeling_Case_Studies_Atmospheric_CO2_and_Electricity_Demand.ipynb, especially its fitting and prediction sections. Trace where the optimized model parameters are represented and check whether the example or related documentation covers saving and continuing training. Done means providing a clear, tested explanation for both workflows or documenting their limitations.