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  • 神经机器翻译(NMT)开源工具

    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。
    ---------------------
    作者:warrioR_wx
    来源:CSDN
    原文:https://blog.csdn.net/wangxinginnlp/article/details/52944432
    版权声明:本文为博主原创文章,转载请附上博文链接!

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  • 原文地址:https://www.cnblogs.com/jfdwd/p/11058614.html
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