Hi! To answer your first question, creating a spaCy model with Word2Vec vectors should be as simple as this:
for word in w2v.wv.vocab:
nlp.vocab.set_vector(word, w2v.wv.word_vec(word))
(The source of the terms.train-vectors
recipe is shipped with Prodigy, so you can also have a look at the code and see how the training plus creating a spaCy model works here).
The init-model
command expects a tab-separated file in the Word2Vec format, where the first line is a string tuple of the shape. See my comment here and this post for more details on the format.