自然语言处理N天-使用Pytorch实现Transformer
https://www.jianshu.com/p/e05ec4bdc60b
https://www.jianshu.com/p/4e94690ba8e3
https://www.jianshu.com/p/2eb21de7fd5f
PaddlePaddle实战 | 千行代码搞定Transformer
Github 上 Star 过千的 NLP 相关项目
https://opennmt.net/OpenNMT-py/main.html#installation
AllenNLP 使用教程
其中的一篇:
https://www.manning.com/books/real-world-natural-language-processing
博客地址：http://blog.csdn.net/wangxinginnlp/article/details/52944432
工具名称：T2T: Tensor2Tensor Transformers
地址：https://github.com/tensorflow/tensor2tensor
语言：Python/Tensorflow
简介：★★★★★ 五颗星
https://research.googleblog.com/2017/06/accelerating-deep-learning-research.html
工具名称：dl4mt
地址：https://github.com/nyu-dl/dl4mt-tutorial/tree/master/session2
语言：Python/Theano
简介：
Attention-based encoder-decoder model for machine translation.
New York University Kyunghyun Cho博士组开发。
工具名称：blocks
地址：https://github.com/mila-udem/blocks
语言：Python/Theano
简介：
Blocks is a framework that helps you build neural network models on top of Theano.
Université de Montréal LISA Lab（实验室主任Yoshua Bengio，实验室现在更名为MILA Lab，主页：https://mila.umontreal.ca/en/）开发，是之前GroundHog（https://github.com/lisa-groundhog/GroundHog）的升级替代版。
工具名称：EUREKA-MangoNMT
地址：https://github.com/jiajunzhangnlp/EUREKA-MangoNMT
语言：C++
简介：A C++ toolkit for neural machine translation for CPU.
中科院自动化所语音语言技术研究组张家俊博士（http://www.nlpr.ia.ac.cn/cip/jjzhang.htm）开发。
工具名称：Nematus
地址：https://github.com/EdinburghNLP/nematus
语言：Python/Theano
简介：爱丁堡大学发布的NMT工具
工具名称：AmuNMT
地址：https://github.com/emjotde/amunmt
语言：C++
简介：
A C++ inference engine for Neural Machine Translation (NMT) models trained with Theano-based scripts from Nematus (https://github.com/rsennrich/nematus) or DL4MT (https://github.com/nyu-dl/dl4mt-tutorial).
Moses Machine Translation CIC公司Hieu Hoang博士（http://statmt.org/~s0565741/）等人开发。
工具名称：Zoph_RNN
地址：https://github.com/isi-nlp/Zoph_RNN
语言：C++
简介：
A C++/CUDA toolkit for training sequence and sequence-to-sequence models across multiple GPUs.
USC Information Sciences Institute开发。
工具名称：sequence-to-sequence mdoels in tensorflow
地址：https://www.tensorflow.org/versions/r0.11/tutorials/seq2seq/index.html
语言：TensorFlow/Python
简介：Sequence-to-Sequence Models
工具名称：nmt_stanford_nlp
地址：http://nlp.stanford.edu/projects/nmt/
语言：Matlab
简介：
Neural machine translation (NMT) at Stanford NLP group.
工具名称：OpenNMT
地址：http://opennmt.net/
语言：Lua/Torch
简介：
OpenNMT was originally developed by Yoon Kim and harvardnlp.
工具名称：lamtram
地址：https://github.com/neubig/lamtram
语言：C++/DyNet
简介：
lamtram: A toolkit for language and translation modeling using neural networks.
CMU Graham Neubig博士组开发。
工具名称：Neural Monkey
地址：https://github.com/ufal/neuralmonkey
语言：TensorFlow/Python
简介：The Neural Monkey package provides a higher level abstraction for sequential neural network models, most prominently in Natural Language Processing (NLP). It is built on TensorFlow. It can be used for fast prototyping of sequential models in NLP which can be used e.g. for neural machine translation or sentence classification.
Institute of Formal and Applied Linguistics at Charles University 开发。
（WMT中NEURAL MT TRAINING TASK用的就是Neural Monkey 见：http://www.statmt.org/wmt17/）
工具名称：Neural Machine Translation (seq2seq) Tutorial
地址：https://github.com/tensorflow/nmt
语言：python/Tensorflow
简介：
Google Brain的Thang Luong博士等人出品
如果对上述工具感兴趣，可以使用WMT16的双语语料跑着玩玩，语料地址 http://www.statmt.org/wmt16/translation-task.html。