From 8b5e3b0d37c66844d2ba0b50348070f45688c4d9 Mon Sep 17 00:00:00 2001
From: Cameron <cysmith1010@gmail.com>
Date: Wed, 2 Nov 2016 00:35:07 -0600
Subject: Update README.md

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 0f5f9c2..dbdece9 100644
--- a/README.md
+++ b/README.md
@@ -131,7 +131,6 @@ Style can be transferred to semantic segmentations in the content image.
 </p>
 
 Multiple styles can be transferred to the foreground and background of the content image.
-
 <p align="center">
 <img src="examples/segmentation/02390.jpg" height="180px">
 <img src="examples/segmentation/basquiat.png" height="180px">
@@ -338,7 +337,7 @@ python neural_style.py --video \
 * `--img_name`: Filename of the output image. *Default*: `result`
 * `--verbose`: Boolean flag indicating if statements should be printed to the console.
 
-"#### Optimization Arguments
+#### Optimization Arguments
 * `--optimizer`: Loss minimization optimizer.  L-BFGS gives better results.  Adam uses less memory. *Choices*: `lbfgs`, `adam`. *Default*: `lbfgs`
 * `--learning_rate`: Learning-rate parameter for the Adam optimizer. *Default*: `1e1`
 * `--max_iterations`: Max number of iterations for the Adam or L-BFGS optimizer. *Default*: `1000`
@@ -366,7 +365,8 @@ python neural_style.py --video \
 
 ## Questions and Errata
 
-Send questions or issues: <img src="examples/equations/email.png">
+Send questions or issues:  
+<img src="examples/equations/email.png">
 
 ## Memory
 By default, `neural-style-tf` uses the NVIDIA cuDNN GPU backend for convolutions and L-BFGS for optimization.
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