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Last pushed: 2 years ago
Short Description
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
Full Description

docker-char-nn

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

Usage

Run docker run -it mbartoli/char-rnn

Persistent checkpoint

  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

Custom training data

  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

Training and sampling

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

More Information

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

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Owner
mbartoli
Source Repository