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TensorFlow implementation of the word2vec (skip-gram model)
My PyTorch implemntation of Skip-Gram Model can be foundhere.
- tensorflow >= 2.0
- numpy >= 1.18
- matplotlib
- tqdm
- nltk
- gensim
python main.pytensorboard --logdir <PATH_TO_TENSORBOARD_EVENTS_FILE>NOTE: By default,PATH_TO_TENSORBOARD_EVENTS_FILE is set toSUMMARY_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 onword2vechere.
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TensorFlow implementation of the word2vec (skip-gram model)
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