ekzhang / Char Rnn Keras
Licence: mit
TensorFlow implementation of multi-layer recurrent neural networks for training and sampling from texts
Stars: ✭ 40
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char-rnn-keras
Multi-layer recurrent neural networks for training and sampling from texts, inspired by Andrej Karpathy's article and the original torch source code karpathy/char-rnn.
Requirements
This code is written in Python 3, and it requires the Keras deep learning library.
Input data
All input data should be placed in the data/ directory. Sample training texts are provided.
Usage
To train the model with default settings:
$ python train.py --input tiny-shakespeare.txt
To sample the model at epoch 100:
$ python sample.py 100
Training loss/accuracy is stored in logs/training_log.csv. Model results, including intermediate model weights during training, are stored in the model directory. These are also used by sample.py for sampling.
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