diff --git a/README.md b/README.md
index 65e11bb..c56b019 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,15 @@
-###<a href="http://arxiv.org/abs/1605.05396">Generative Adversarial Text-to-Image Synthesis</a>
+### <a href="http://arxiv.org/abs/1605.05396">Generative Adversarial Text-to-Image Synthesis</a>
 Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee
 
 This is the code for our ICML 2016 paper on text-to-image synthesis using conditional GANs. You can use it to train and sample from  text-to-image models. The code is adapted from the excellent [dcgan.torch](https://github.com/soumith/dcgan.torch).
 
 <img src="images/dcgan_network.jpg" width="900px" height="220px"/>
 
-####Setup Instructions
+#### Setup Instructions
 
 You will need to install [Torch](http://torch.ch/docs/getting-started.html), CuDNN, and the [display](https://github.com/szym/display) package.
 
-####How to train a text to image model:
+#### How to train a text to image model:
 
 1. Download the [birds](https://drive.google.com/file/d/0B0ywwgffWnLLLUc2WHYzM0Q2eWc/view?usp=sharing) and [flowers](https://drive.google.com/file/d/0B0ywwgffWnLLMl9uOU91MV80cVU/view?usp=sharing) and [COCO](https://drive.google.com/open?id=0B0ywwgffWnLLamltREhDRjlaT3M) caption data in Torch format.
 2. Download the [birds](http://www.vision.caltech.edu/visipedia/CUB-200-2011.html) and [flowers](http://www.robots.ox.ac.uk/~vgg/data/flowers/102) and [COCO](http://mscoco.org/dataset/#download) image data.
@@ -17,7 +17,7 @@ You will need to install [Torch](http://torch.ch/docs/getting-started.html), CuD
 4. Modify the `CONFIG` file to point to your data and text encoder paths.
 5. Run one of the training scripts, e.g. `./scripts/train_cub.sh`
 
-####How to generate samples:
+#### How to generate samples:
 
 * For flowers: `./scripts/demo_flowers.sh`. Add text descriptions to `scripts/flowers_queries.txt`.
 * For birds: `./scripts/demo_cub.sh`.
@@ -28,19 +28,19 @@ You will need to install [Torch](http://torch.ch/docs/getting-started.html), CuD
 <img src="images/flowers_samples.jpg" width="900px" height="450px"/>
 <img src="images/cub_samples.jpg" width="900px" height="450px"/>
 
-####Pretrained models:
+#### Pretrained models:
 
 * [CUB GAN-INT-CLS](https://drive.google.com/open?id=0B0ywwgffWnLLSW84ZXRjdXhObzQ)
 * [Flowers GAN-INT-CLS](https://drive.google.com/open?id=0B0ywwgffWnLLV0U4MGwzZ2JKT3c)
 * [COCO GAN-CLS](https://drive.google.com/open?id=0B0ywwgffWnLLT0JqcEFrOG1iVVk)
 
-####How to train a text encoder from scratch:
+#### How to train a text encoder from scratch:
 
 * You may want to do this if you have your own new dataset of text descriptions.
 * For flowers and birds: follow the instructions [here](https://github.com/reedscot/cvpr2016).
 * For MS-COCO: `./scripts/train_coco_txt.sh`.
 
-####Citation
+#### Citation
 
 If you find this useful, please cite our work as follows: