word2vec-ruscorpora-300

Word2vec Continuous Skipgram vectors trained on the full Russian National Corpus (about 250M words).

Related issue #3.

attribute	value
File size	199MB
Number of vectors	184973
Preprocessing	The corpus (used for training) was lemmatized and tagged with Universal PoS
Window size	10
Dimension	300
License	https://creativecommons.org/licenses/by/4.0/deed.en

Read more:

• https://www.academia.edu/24306935/WebVectors_a_Toolkit_for_Building_Web_Interfaces_for_Vector_Semantic_Models
• http://rusvectores.org/en/

Example

import gensim.downloader as api

model = api.load("word2vec-ruscorpora-300")
for word, distance in model.most_similar(u"кот_NOUN"):  
    print(u"{}: {:.3f}".format(word, distance))
  
"""
output:

кошка_NOUN: 0.757
котенок_NOUN: 0.668
пес_NOUN: 0.563
мяукать_VERB: 0.562
тобик_NOUN: 0.559
фоксик_NOUN: 0.557
собака_NOUN: 0.557
мяучать_VERB: 0.554
харлашка_NOUN: 0.552
котяра_NOUN: 0.551
"""