A simple LSTM based Statement of Purpose Generator for grad school. :)
- Pytorch 0.4
- Python 2.x / 3.x
Generate samples from the trained model.
python generate.py --data ./data/sop/ --seed 6 # play with seed to get different text
python main.py --cuda --epochs 500 --data data/sop/ --tied # Train a tied LSTM on SOP dataset with CUDA for 500 epochs
The model uses the nn.RNN
module (and its sister modules nn.GRU
and nn.LSTM
)
which will automatically use the cuDNN backend if run on CUDA with cuDNN installed.
During training, if a keyboard interrupt (Ctrl-C) is received, training is stopped and the current model is evaluated against the test dataset.