My training data set has become large, and training is now taking over 1 hour. Training time is now having a major impact of developer productivity. In order to reduce training time, I would like to train my NLU model and Core model separately and in parallel. While Rasa allows me to train separately, I don’t see a way to load them separately without having two separate services running. Ideally I would like to do something like this
$ rasa run --core <core_model> --nlu <nlu_model>
Are there any ways to achieve this?