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content/learning-paths/smartphones-and-mobile/Build-Llama3-Chat-Android-App-Using-Executorch-And-XNNPACK/_index.md

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title: Build an Android chat app with Llama, ExecuTorch, and XNNPACK
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title: Build an Android chat app with Llama, KleidiAI, ExecuTorch, and XNNPACK
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minutes_to_complete: 60
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who_is_this_for: This is an introductory topic for software developers interested in learning how to build an Android chat app with Llama, ExecuTorch, and XNNPACK.
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who_is_this_for: This is an introductory topic for software developers interested in learning how to build an Android chat app with Llama, KleidiAI, ExecuTorch, and XNNPACK.
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learning_objectives:
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- Set up an ExecuTorch development environment.
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- Describe how ExecuTorch uses XNNPACK kernels to accelerate performance on Arm-based platforms.
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- Describe how ExecuTorch uses KleidiAI kernels to accelerate performance on Arm-based platforms.
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- Describe how 4-bit groupwise PTQ quantization reduces model size without significantly sacrificing model accuracy.
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- Build and run Llama models using ExecuTorch on your development machine.
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- Build and run an Android Chat app with different Llama models using ExecuTorch on an Arm-based smartphone.
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prerequisites:
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- An Apple M1/M2 development machine with Android Studio installed or a Linux machine with at least 16GB of RAM.
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- An Arm-powered smartphone running Android, with 16GB of RAM.
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- An Arm-powered smartphone with the i8mm feature running Android, with 16GB of RAM.
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- A USB cable to connect your smartphone to your development machine.
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- Android Debug Bridge (adb) installed on your device. Follow the steps in [adb](https://developer.android.com/tools/adb) to install Android SDK Platform Tools. The adb tool is included in this package.
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- Java 17 JDK. Follow the steps in [Java 17 JDK](https://www.oracle.com/java/technologies/javase/jdk17-archive-downloads.html) to download and install JDK for host.
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- Python 3.10.
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author_primary: Varun Chari
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author_primary: Varun Chari, Pareena Verma
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### Tags
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skilllevels: Introductory

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