Word2Vec skipgram trainer.py

# coding: utf-8

# In[27]:

import gensim, logging
import os



os.chdir('C:\\Users\\rounayak\\Documents\\Fuso\\word embedding\\word to vec\\Summing')
#logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
 
class MySentences(object):
    def __init__(self, dirname):
        self.dirname = dirname
 
    def __iter__(self):
        for fname in os.listdir(self.dirname):
            for line in open(os.path.join(self.dirname, fname), encoding='utf-8'):
                yield line.split()
 
sentences = MySentences('C:/Users/rounayak/Documents/Fuso/word embedding/word to vec/Summing/train')
                    


# In[23]:

iter(sentences)


# In[40]:

model = gensim.models.Word2Vec(sentences, size=300, window=5, min_count=3, workers=4,sg=1)


# In[41]:


model.save('C:/Users/rounayak/Documents/Fuso/word2vec/Word2Vec')



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