Skip Gram Model PyTorch Save
PyTorch implementation of the Word2Vec (Skip-Gram Model) and visualizing the trained embeddings using TSNE
Project README
Skip-Gram-Model-PyTorch
PyTorch implementation of the word2vec (skip-gram model) and visualization of the trained embeddings using TSNE !
My TensorFlow implemntation of Skip-Gram Model can be found here.
Requirements
- torch >= 1.4
- numpy >= 1.18
- matplotlib
- tqdm
- nltk
- gensim
Training
python main.py
Visualizing real-time training loss in Tensorboard
tensorboard --logdir <PATH_TO_TENSORBOARD_EVENTS_FILE>
NOTE: By default, PATH_TO_TENSORBOARD_EVENTS_FILE is set to SUMMARY_DIR in config.py
Testing
python test.py
Inference
| war | india | crime | guitar | movies | desert | physics | religion | football | computer |
|---|---|---|---|---|---|---|---|---|---|
| fight | europe | despite | band | movie | region | theory | religious | team | program |
| battle | central | help | play | series | along | mathematics | christian | win | systems |
| army | western | seek | record | show | western | mathematical | regard | sport | available |
| force | indian | challenge | piece | film | southern | study | tradition | club | design |
| ally | part | fail | star | feature | plain | science | christianity | league | information |
Blog-Post
Check out my blog post on word2vec here.
Open Source Agenda is not affiliated with "Skip Gram Model PyTorch" Project. README Source: n0obcoder/Skip-Gram-Model-PyTorch
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3 years ago
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