How to load a pre-trained Word2vec MODEL File and reuse it?

Question

I want to use a pre-trained word2vec model, but I don't know how to load it in python.

This file is a MODEL file (703 MB). It can be downloaded here:
http://devmount.github.io/GermanWordEmbeddings/

Answer 1

just for loading

import gensim

# Load pre-trained Word2Vec model.
model = gensim.models.Word2Vec.load("modelName.model")

now you can train the model as usual. also, if you want to be able to save it and retrain it multiple times, here's what you should do

model.train(//insert proper parameters here//)
"""
If you don't plan to train the model any further, calling
init_sims will make the model much more memory-efficient
If `replace` is set, forget the original vectors and only keep the normalized
ones = saves lots of memory!
replace=True if you want to reuse the model
"""
model.init_sims(replace=True)

# save the model for later use
# for loading, call Word2Vec.load()

model.save("modelName.model")

Answer 2

Use KeyedVectors to load the pre-trained model.

from gensim.models import KeyedVectors
from gensim import models

word2vec_path = 'path/GoogleNews-vectors-negative300.bin.gz'
w2v_model = models.KeyedVectors.load_word2vec_format(word2vec_path, binary=True)

Answer 3

I used the same model in my code and since I couldn't load it, I asked the author about it. His answer was that the model has to be loaded in binary format:

gensim.models.KeyedVectors.load_word2vec_format(w2v_path, binary=True)

This worked for me, and I think it should work for you, too.