Multi-layer RNN (LSTM, GRU, RNN) for character-level language models in Blocks
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LICENSE
README.md
config.py
make_dataset.py
model.py
sample.py
train.py
utils.py

README.md

char-rnn in Blocks

This code is a python implementation of Torch char-rnn project using the Blocks framework.

Requirements

  • Install Blocks. Please see the documentation for more information.

Usage

  • Set text_file parameter in the config.py file. You can try the input.txt file used in the original code.
  • run make_dataset.py to create the Fuel dataset.
  • run train.py file to train a Gated RNN (Cho et al.). 'rnn' and 'lstm' are also supported.
  • run sample.py to sample characters using a trained model.

train.py and sample.py scripts follow most of the parameters from the original char-rnn project. Please take a look on it to train your own models.