Awesome
Chainer example code for NLP
This repository is out of date and rough. I do not guarantee that these code works correctly.
I am developing a new NMT toolkit NMTKit and strongly recommend to use it instead of these samples to train neural translation models.
This repository contains some neural network examples for natural language processing (NLP) using Chainer framework.
Making Local Client
Before running these scripts, making a local python client using pyenv
is
reccomended, like:
$ pyenv install 3.5.0
$ pyenv virtualenv 3.5.0 example
$ pyenv shell example
$ pip install chainer
Contents
-
Machine Translation
mt_s2s_encdec.py
- Using encoder-decoder style recurrent neural networkmt_s2s_attention.py
- Using attentional neural network
-
Word Segmentation (Tokenization)
seg_ffnn.py
- Using feedforward neural networkseg_rnn.py
- Using recurrent neural network
-
Language Model
lm_rnn.py
- Using recurrent neural network (RNNLM)
Contact
If you find an issue or have some questions, please contact Yusuke Oda:
- @odashi_t on Twitter (faster than other methods)
- yus.takara (at) gmail.com