Several Spark ML components already allow setting of an initial model, including KMeans, LogisticRegression, and GaussianMixture. This is useful to begin training from a known reasonably good model.
However, the method in LogisticRegression is private to Spark. I don't see a good reason why it should be as the others in KMeans et al are not.
None of these are exposed in Pyspark, which I don't necessarily want to question or deal with now; there are other places one could arguably set an initial model too, but, here just interested in exposing the existing, tested functionality to callers.