
from gensim.models.keyedvectors import KeyedVectors

word_vectors = KeyedVectors.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)

word_vectors.save_word2vec_format('./GoogleNews-vectors-negative300.txt', fvocab='GoogleNews-vectors-negative300_vocab.txt', binary=False)

