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-rw-r--r-- | README.md | 2 |
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@@ -53,7 +53,7 @@ TfLite will then delegate operations, that can be accelerated with Arm NN, to Ar executed with the usual TfLite runtime. This is our **recommended way to accelerate TfLite models**. As with our parsers there are tutorials in our doxygen documentation that can be found in the [wiki section](https://github.com/ARM-software/armnn/wiki/Documentation). -If you would like to use **Arm NN on Android** you can follow this guide which explains [how to build Arm NN using the AndroidNDK](). +If you would like to use **Arm NN on Android** you can follow this guide which explains [how to build Arm NN using the AndroidNDK](BuildGuideAndroidNDK.md). But you might also want to take a look at another repository which implements a hardware abstraction layer (HAL) for Android. The repository is called [Android-NN-Driver](https://github.com/ARM-software/android-nn-driver) and when integrated into Android it will automatically run neural networks with Arm NN. |