Japanese text8 corpus for word embedding.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
.gitignore Initial commit Oct 4, 2017
README.md change license Oct 4, 2017
process.py Initial commit Oct 4, 2017
setup.sh Initial commit Oct 4, 2017
tokenize.py Initial commit Oct 4, 2017



ja.text8 is a small (100MB) text corpus from the web (japanese wikipedia).

You can download ja.text8 corpus from the following link:


You can train word2vec by ja.text8. After downloading ja.text8, run the following code. It takes about 2 minutes to finish training:

import logging
from gensim.models import word2vec

logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
sentences = word2vec.Text8Corpus('ja.text8')
model = word2vec.Word2Vec(sentences, size=200)

After the training, you can test the model as follows:

>>> model.most_similar(['日本'])
[('中国', 0.598496675491333),
 ('韓国', 0.5914819240570068),
 ('アメリカ', 0.5286925435066223),
 ('英国', 0.5090063810348511),
 ('台湾', 0.4761126637458801),
 ('米国', 0.45954638719558716),
 ('アメリカ合衆国', 0.45181626081466675),
 ('イギリス', 0.44740626215934753),
 ('ソ連', 0.43657147884368896),
 ('海外', 0.4325913190841675)]



  • Python 3.x
  • MeCab
  • virtualenv

Make corpus by yourself

You can download ja.text8. But you can make the corpus by yourself.

Simply run:

$ ./setup.sh