From e78e38bd9b0b4d852804d88ad9336c6385b90d43 Mon Sep 17 00:00:00 2001
From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
Date: Sat, 14 Dec 2024 22:18:39 +0000
Subject: [PATCH] Space typo

---
 .../profiling-ml-on-arm/nn-profiling-executenetwork.md          | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/content/learning-paths/smartphones-and-mobile/profiling-ml-on-arm/nn-profiling-executenetwork.md b/content/learning-paths/smartphones-and-mobile/profiling-ml-on-arm/nn-profiling-executenetwork.md
index 1679673b2..323d72367 100644
--- a/content/learning-paths/smartphones-and-mobile/profiling-ml-on-arm/nn-profiling-executenetwork.md
+++ b/content/learning-paths/smartphones-and-mobile/profiling-ml-on-arm/nn-profiling-executenetwork.md
@@ -15,7 +15,7 @@ If you are using LiteRT without Arm NN, then the output from `ExecuteNetwork` is
 
 To try this out, you can download a LiteRT model from the [Arm Model Zoo](https://github.com/ARM-software/ML-zoo). Specifically for this Learning Path, you will download [mobilenet tflite](https://github.com/ARM-software/ML-zoo/blob/master/models/image_classification/mobilenet_v2_1.0_224/tflite_int8/mobilenet_v2_1.0_224_INT8.tflite).
 
-### Download and setup ExecuteNetwork
+### Download and set up ExecuteNetwork
 
 You can download `ExecuteNetwork` from the [Arm NN GitHub](https://github.com/ARM-software/armnn/releases). Download the version appropriate for the Android phone that you are testing on, ensuring that it matches the Android version and architecture of the phone. If you are unsure of the architecture, you can use a lower one, but you might miss out on some optimizations.`ExecuteNetwork` is included inside the `tar.gz` archive that you download. Among the other release downloads on the Arm NN Github is a separate file for the `aar` delegate which you can also easily download.