I\'ve tried several methods of loading the google news word2vec vectors (https://code.google.com/archive/p/word2vec/):
en_nlp = spacy.load(\'en\',vector=Fals
it is much easier to use the gensim api for dowloading the word2vec compressed model by google, it will be stored in /home/"your_username"/gensim-data/word2vec-google-news-300/
. Load the vectors and play ball. I have 16GB of RAM which is more than enough to handle the model
import gensim.downloader as api
model = api.load("word2vec-google-news-300") # download the model and return as object ready for use
word_vectors = model.wv #load the vectors from the model