SpaCy: how to load Google news word2vec vectors?

Question

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         


        

Answer 1

I know that this question has already been answered, but I am going to offer a simpler solution. This solution will load google news vectors into a blank spacy nlp object.

import gensim
import spacy

# Path to google news vectors
google_news_path = "path\to\google\news\\GoogleNews-vectors-negative300.bin.gz"

# Load google news vecs in gensim
model = gensim.models.KeyedVectors.load_word2vec_format(gn_path, binary=True)

# Init blank english spacy nlp object
nlp = spacy.blank('en')

# Loop through range of all indexes, get words associated with each index.
# The words in the keys list will correspond to the order of the google embed matrix
keys = []
for idx in range(3000000):
    keys.append(model.index2word[idx])

# Set the vectors for our nlp object to the google news vectors
nlp.vocab.vectors = spacy.vocab.Vectors(data=model.syn0, keys=keys)

>>> nlp.vocab.vectors.shape
(3000000, 300)