Added blog post "Learn how to develop Android applications with ExecuTorch and Llama models" (#1669)

* Added blog post "Learn how to develop Android applications with ExecuTorch and Llama models"

Signed-off-by: Chris Abraham <[email protected]>

* Update and rename 2024-07-09-develop-android-applications.md to 2024-07-10-develop-android-applications.md

Signed-off-by: Kylie Wagar-Dirks <[email protected]>

---------

Signed-off-by: Chris Abraham <[email protected]>
Signed-off-by: Kylie Wagar-Dirks <[email protected]>
Co-authored-by: Kylie Wagar-Dirks <[email protected]>

Author: cjyabraham

_posts/2024-07-10-develop-android-applications.md

@@ -0,0 +1,40 @@
+---
+layout: blog_detail
+title: "Learn how to develop Android applications with ExecuTorch and Llama models"
+---
+_This blog is courtesy of the PyTorch team at Arm. More details can be found [here]([url](https://learn.arm.com/learning-paths/smartphones-and-mobile/build-llama3-chat-android-app-using-executorch-and-xnnpack/?utm_source=twitter&utm_medium=social-organic&utm_content=landingpage&utm_campaign=mk24_developer_na))._
+
+Arm’s compute platform is delivering GenAI applications on phones, laptops, and servers. Cost, privacy, performance, security, and energy efficiency are just some of the reasons developers are investigating on-device AI. 
+
+A new Learning Path explaining how to leverage the capabilities of large language models (LLMs) on Android using ExecuTorch and XNNPACK is now available.
+
+Here's a summary of what you'll learn:
+
+* Development Environment setup
+
+    The Learning Path begins by guiding you through setting up your development environment, ensuring you have all the necessary tools installed, including Android Studio, the Android NDK, Java JDK, and Python.
+
+* ExecuTorch and XNNPACK
+
+    You'll learn about the core technologies: ExecuTorch, a framework for deploying PyTorch models to edge devices, and XNNPACK, a high-performance library for executing neural networks on Arm-based platforms.
+
+* Llama models
+
+    The Learning Path explores Llama, a family of powerful LLMs, focusing specifically on the 8B Llama 3 model. You'll learn about quantization techniques, which are essential for optimizing model size and performance on mobile devices.
+
+* Prepare Llama models for ExecuTorch
+
+    You'll be guided through the process of downloading, exporting, and evaluating Llama models, ensuring they are ready for deployment using ExecuTorch.
+
+* Check model performance on Android
+
+    The Learning Path walks you through cross-compiling the Llama runner binary for Android, allowing you to test your model's performance on your phone.
+
+* Build and run an Android Chat App
+
+    Finally, you'll learn how to build a native Android chat app using the `LlamaDemo` application from the ExecuTorch repository. This hands-on experience allows you to put your knowledge into practice and create a real-world application.
+
+
+Explore this Learning Path if you want to learn how to leverage the power of LLMs on your Android phone, and gain expertise in tools for on-device machine learning. 
+
+Dig into the excitement of building Android chat apps and understand more about how they work on the [Arm Developer Hub]([url](https://learn.arm.com/learning-paths/smartphones-and-mobile/build-llama3-chat-android-app-using-executorch-and-xnnpack/?utm_source=twitter&utm_medium=social-organic&utm_content=landingpage&utm_campaign=mk24_developer_na)).