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=False)
en_nlp.vocab.load_vectors_from_bin_loc('GoogleNews-vectors-negative300.bin')

The above gives:

MemoryError: Error assigning 18446744072820359357 bytes

I've also tried with the .gz packed vectors; or by loading and saving them with gensim to a new format:

from gensim.models.word2vec import Word2Vec
model = Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)
model.save_word2vec_format('googlenews2.txt')

This file then contains the words and their word vectors on each line. I tried to load them with:

en_nlp.vocab.load_vectors('googlenews2.txt')

but it returns "0".

What is the correct way to do this?

Update:

I can load my own created file into spacy. I use a test.txt file with "string 0.0 0.0 ...." on each line. Then zip this txt with .bzip2 to test.txt.bz2. Then I create a spacy compatible binary file:

spacy.vocab.write_binary_vectors('test.txt.bz2', 'test.bin')

That I can load into spacy:

nlp.vocab.load_vectors_from_bin_loc('test.bin')

This works! However, when I do the same process for the googlenews2.txt, I get the following error:

lib/python3.6/site-packages/spacy/cfile.pyx in spacy.cfile.CFile.read_into (spacy/cfile.cpp:1279)()

OSError: 

Answer 1

For spacy 1.x, load Google news vectors into gensim and convert to a new format (each line in .txt contains a single vector: string, vec):

from gensim.models.word2vec import Word2Vec
from gensim.models import KeyedVectors
model = KeyedVectors.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)
model.wv.save_word2vec_format('googlenews.txt')

Remove the first line of the .txt:

tail -n +2 googlenews.txt > googlenews.new && mv -f googlenews.new googlenews.txt

Compress the txt as .bz2:

bzip2 googlenews.txt

Create a SpaCy compatible binary file:

spacy.vocab.write_binary_vectors('googlenews.txt.bz2','googlenews.bin')

Move the googlenews.bin to /lib/python/site-packages/spacy/data/en_google-1.0.0/vocab/googlenews.bin of your python environment.

Then load the wordvectors:

import spacy
nlp = spacy.load('en',vectors='en_google')

or load them after later:

nlp.vocab.load_vectors_from_bin_loc('googlenews.bin')