From the word2vec site I can download GoogleNews-vectors-negative300.bin.gz. The .bin file (about 3.4GB) is a binary format not useful to me. Tomas Mikolov assures us that "It should be fairly straightforward to convert the binary format to text format (though that will take more disk space). Check the code in the distance tool, it's rather trivial to read the binary file." Unfortunately, I don't know enough C to understand http://word2vec.googlecode.com/svn/trunk/distance.c.
Supposedly gensim can do this also, but all the tutorials I've found seem to be about converting from text, not the other way.
Can someone suggest modifications to the C code or instructions for gensim to emit text?
I use this code to load binary model, then save the model to text file,
from gensim.models.keyedvectors import KeyedVectors
model = KeyedVectors.load_word2vec_format('path/to/GoogleNews-vectors-negative300.bin', binary=True)
model.save_word2vec_format('path/to/GoogleNews-vectors-negative300.txt', binary=False)
Note:
Above code is for new version of gensim. For previous version, I used this code:
from gensim.models import word2vec
model = word2vec.Word2Vec.load_word2vec_format('path/to/GoogleNews-vectors-negative300.bin', binary=True)
model.save_word2vec_format('path/to/GoogleNews-vectors-negative300.txt', binary=False)