changes in README

README.md

@@ -1,14 +1,13 @@
 Deep Networks with Stochastic Depth
 ====================
 This repository hosts the Torch 7 code for the paper _Deep Networks with Stochastic Depth_
-available at http://arxiv.org/abs/1603.09382v1.
-The code in `code_cifar/` reproduces the results in Figure 3 on CIFAR-10 and CIFAR-100. The code for SVHN and 1202-layer CIFAR-10 (which requires some special memory optimization) will be available very soon.
+available at http://arxiv.org/abs/1603.09382v1. For now, the code reproduces the results in Figure 3 on CIFAR-10 and CIFAR-100. The code for SVHN and 1202-layer CIFAR-10 (which requires some memory optimization) will be available very soon.
 
 ### Prerequisites
 - Torch 7 and CUDA with the basic packages (nn, optim, cutorch, cunn)
 - cudnn (https://developer.nvidia.com/cudnn) and torch bindings (https://github.com/soumith/cudnn.torch)
 - nninit torch package (https://github.com/Kaixhin/nninit)
-- CIFAR-10 and CIFAR-100 dataset in Torch format, this script https://github.com/soumith/cifar.torch would very conveniently handle it for you
+- CIFAR-10 and CIFAR-100 dataset in Torch format, this script https://github.com/soumith/cifar.torch should very conveniently handle it for you
 
 ### Getting Started
 This command runs the 110-layer ResNet on CIFAR-10 with stochastic depth, using linear decaying survival probabilities ending in 0.5 <br/>
@@ -20,5 +19,3 @@ You can run on CIFAR-100 by adding the flag `-dataset cifar100`.
 
 ### Contact
 My email is ys646 at cornell.edu. I'm happy to answer any of your question, and I'd very much appreciate your suggestions. 
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