Docker container for use with Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

Run docker run -it mbartoli/char-rnn

1. Create a folder cv to persist training data with mkdir cv.
2. Mount the folder into the container and run it:
   docker run -v $(pwd)/cv:/home/char-rnn/cv -it mbartoli/char-rnn
3. Train your char-rnn

1. Create a folder containing some training data.
   mkdir -p data/my-training-data
2. Run the container with the new training data and cv folder mounted
   docker run -v $(pwd)/cv:/home/char-rnn/cv -v $(pwd)/data/my-training-data:/home/char-rnn/data/my-training-data -it mbartoli/char-rnn
3. Train your char-rnn

See the documentation on how to train and sample your char-rnn.

https://github.com/karpathy/char-rnn
http://karpathy.github.io/2015/05/21/rnn-effectiveness/