I wanted to reduce the training time while using the Nested Model. So is there a way/provision to do some parallel processing like training different parts of the model separately and once they are learnt then combining them?
For example: I can learn one state on one machine and another on another and then combine the two by adding edge/transition features to the combined model or something like that..

Thanking in anticipation