How to initialize a new word2vec model with pre-trained model weights?

Question

I am using Gensim Library in python for using and training word2vector model. Recently, I was looking at initializing my model weights with some pre-trained word2vec model such as (GoogleNewDataset pretrained model). I have been struggling with it couple of weeks. Now, I just searched out that in gesim there is a function that can help me to initialize the weights of my model with pre-trained model weights. That is mentioned below:

reset_from(other_model)

    Borrow shareable pre-built structures (like vocab) from the other_model. Useful if testing multiple models in parallel on the same corpus.

I don't know this function can do the same thing or not. Please help!!!

Answer 1

You can now do incremental training with gensim. I would recommend loading the pretrained model and then doing an update.

from gensim.models import Word2Vec

model = Word2Vec.load('pretrained_model.emb')
model.build_vocab(new_sentences, update=True)
model.train(new_sentences)