karpathy's char-rnn implementation by Chainer
$ pip install chainer
Start training the model using train.py
, for example
$ python train.py
The --data_dir
flag specifies the dataset to use. By default it is set to data/tinyshakespeare
which consists of a subset of works of Shakespeare.
Your own data: If you'd like to use your own data create a single file input.txt
and place it into a folder in data/
. For example, data/some_folder/input.txt
.
Given a checkpoint file (such as those written to cv) we can generate new text. For example:
$ python sample.py \
--vocabulary data/tinyshakespeare/vocab.bin \
--model cv/some_checkpoint.chainermodel \
--primetext some_text --gpu -1
- Original implementation: https://github.com/karpathy/char-rnn
- Blog post: http://karpathy.github.io/2015/05/21/rnn-effectiveness/