Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow.
Inspired from Andrej Karpathy's char-rnn.
#Updated By jeremy Ellis twitter @rocksetta Oct 24, 2016
Getting this working on cloud9 http://c9.io and with php support so that it can be done from a web page
Setup by making a blank workspace and running the setup.sh bash file.
Install this github
I use a blank workspace but php5 or python would probably work.
To setup pythyon
right click --> run setup.py
To run the web server
Right click --> run the rnn-both.php file
(for a simple situtaion use rnn-serve.php with rnn-serve.html)
Open the link provided in the terminal output
I also have a github for installing both Magenta and this github onto cloud9 at
use at your own risk! .
back to the original readme.md
To train with default parameters on the tinyshakespeare corpus, run
To sample from a checkpointed model,
- Add explanatory comments
- Expose more command-line arguments
- Compare accuracy and performance with char-rnn