Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow.
Inspired from Andrej Karpathy's char-rnn.
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The website about it is here https://www.rocksetta.com/tensorflow-teacher/3d-print-tensorflow/
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#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
https://github.com/hpssjellis/char-rnn-tensorflow-music-3dprinting.git
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
https://github.com/hpssjellis/my-tensorflow-magenta-online
use at your own risk! .
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back to the original readme.md
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To train with default parameters on the tinyshakespeare corpus, run python train.py.
To sample from a checkpointed model, python sample.py.
- Add explanatory comments
- Expose more command-line arguments
- Compare accuracy and performance with char-rnn