TensorFlow implementation of the word2vec (skip-gram model)
My PyTorch implemntation of Skip-Gram Model can be found here.
- tensorflow >= 2.0
- numpy >= 1.18
- matplotlib
- tqdm
- nltk
- gensim
python main.py
tensorboard --logdir <PATH_TO_TENSORBOARD_EVENTS_FILE>
NOTE: By default, PATH_TO_TENSORBOARD_EVENTS_FILE is set to SUMMARY_DIR in config.py
tensorboard dev upload--logdir <PATH_TO_TENSORBOARD_EVENTS_FILE>
python test.py
war | india | crime | guitar | movies | desert | physics | religion | football | computer |
---|---|---|---|---|---|---|---|---|---|
invasion | provinces | will | bass | movie | shore | mathematics | judaism | baseball | digital |
soviet | pakistan | prosecution | drum | albums | hilly | mathematical | islam | championship | computers |
troop | mainland | accusations | solo | songs | plateau | chemistry | religions | basketball | software |
army | asian | provoke | quartet | cartoon | basin | theoretical | religious | coach | electronic |
ally | colonial | prosecute | vocals | animate | highlands | analysis | jewish | wrestler | interface |
Check out my blog post on word2vec here.