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12 changes: 4 additions & 8 deletions docs/source/android-prebuilt-library.md
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# Using Android prebuilt libraries (AAR)
# Using Android prebuilt library (AAR)

We provide two prebuilt Android libraries (AAR), `executorch.aar` for generic use case (image/audio processing) and `executorch_llama.aar` for LLAMA use case.
We provide a prebuilt Android library (AAR), `executorch.aar` for both generic (image/audio processing) and LLAMA use case.

## Contents of libraries
## Contents of library
- `executorch.aar`
- [Java library](https://github.com/pytorch/executorch/tree/main/extension/android/src/main/java/org/pytorch/executorch)
- JNI contains the JNI binding for [NativePeer.java](https://github.com/pytorch/executorch/blob/main/extension/android/src/main/java/org/pytorch/executorch/NativePeer.java) and ExecuTorch native library, including core ExecuTorch runtime libraries, XNNPACK backend, Portable kernels, Optimized kernels, and Quantized kernels.
- Comes with two ABI variants, arm64-v8a and x86_64.
- `executorch_llama.aar`
- [Java library](https://github.com/pytorch/executorch/tree/main/extension/android/src/main/java/org/pytorch/executorch) (Note: it contains the same Java classes as the previous Java, but it does not contain the JNI binding for generic Module/NativePeer Java code).
- JNI contains the JNI binding for [LlamaModule.java](https://github.com/pytorch/executorch/blob/main/extension/android/src/main/java/org/pytorch/executorch/LlamaModule.java) and ExecuTorch native library, including core ExecuTorch runtime libraries, XNNPACK backend, Portable kernels, Optimized kernels, Quantized kernels, and LLAMA-specific Custom ops library.
- JNI contains the JNI binding for the corresponding Java code, and ExecuTorch native library, including core ExecuTorch runtime libraries, XNNPACK backend, Portable kernels, Optimized kernels, Quantized kernels, and LLAMA-specific Custom ops library.
- Comes with two ABI variants, arm64-v8a and x86_64.

## Downloading AAR
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