Transform google-pretrained (C format) to gensim format (python)

1. Download pretrained file (Reference)
2. Run frombin2gensim.py

./frombin2gensim.py # will generate google_word2vec_pretrained

Train word embedding from raw corpus

1. Run train_from_corpus.py

./train_from_corpus.py corpus model_output 

Use word embedding in your project

from gensim.models import Word2Vec as W2V
model_path = 'path/to/embedding_model'
w2v = W2V.load(model_path)