Update README.md

README.md

@@ -12,7 +12,7 @@ Its goal is to provide researchers:
 
 Over 20 tasks are supported in the first release, including popular datasets such as [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/), [bAbI tasks](https://arxiv.org/abs/1502.05698), [MCTest](https://www.microsoft.com/en-us/research/publication/mctest-challenge-dataset-open-domain-machine-comprehension-text/), [WikiQA](https://www.microsoft.com/en-us/download/details.aspx?id=52419), [WebQuestions](http://www.aclweb.org/anthology/D13-1160), [SimpleQuestions](https://arxiv.org/abs/1506.02075), [WikiMovies](https://arxiv.org/abs/1606.03126), [QACNN & QADailyMail](https://arxiv.org/abs/1506.03340), [CBT](https://arxiv.org/abs/1511.02301), [BookTest](https://arxiv.org/abs/1610.00956), [bAbI Dialog tasks](https://arxiv.org/abs/1605.07683), [Ubuntu Dialog](https://arxiv.org/abs/1506.08909), [OpenSubtitles](http://opus.lingfil.uu.se/OpenSubtitles.php), [Cornell Movie](https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html) and [VQA-COCO2014](http://visualqa.org/).
 
-Included are examples of training neural models with [PyTorch](http://pytorch.org/) and [Lua Torch](http://torch.ch/), including both batch training on GPU and hogwild training on CPUs. Using [Theano](http://deeplearning.net/software/theano/) or [Tensorflow](https://www.tensorflow.org/) instead is also straightforward.
+Included are examples of training neural models with [PyTorch](http://pytorch.org/) and [Lua Torch](http://torch.ch/), with batch training on GPU or hogwild training on CPUs. Using [Theano](http://deeplearning.net/software/theano/) or [Tensorflow](https://www.tensorflow.org/) instead is also straightforward.
 
 Our aim is for the number of tasks and agents that train on them to grow in a community-based way.