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updates for prerequisites and converting model pages
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content/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/1-prerequisites.md

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@@ -78,16 +78,26 @@ Bazel is an open-source build tool which you will use to build LiteRT libraries.
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{{< tabpane code=true >}}
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{{< tab header="Linux">}}
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cd $WORKSPACE
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wget https://github.com/bazelbuild/bazel/releases/download/7.4.1/bazel-7.4.1-installer-linux-x86_64.sh
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export BAZEL_VERSION=7.4.1
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wget https://github.com/bazelbuild/bazel/releases/download/{$BAZEL_VERSION}/bazel-{$BAZEL_VERSION}-installer-linux-x86_64.sh
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sudo bash bazel-7.4.1-installer-linux-x86_64.sh
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export PATH="/usr/local/bin:$PATH"
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{{< /tab >}}
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{{< tab header="MacOS">}}
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cd $WORKSPACE
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export BAZEL_VERSION=7.4.1
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curl -fLO "https://github.com/bazelbuild/bazel/releases/download/{$BAZEL_VERSION}/bazel-{$BAZEL_VERSION}-installer-darwin-arm64.sh"
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sudo bash bazel-7.4.1-installer-darwin-arm64.sh
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export PATH="/usr/local/bin:$PATH"
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{{< /tab >}}
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{{< /tabpane >}}
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You can verify the installation and check the version with:
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```console
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bazel --version
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```
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### Install Android NDK
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To run the model on Android, install Android Native Development Kit (Android NDK):
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unzip android-ndk-r25b-linux.zip
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{{< /tab >}}
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{{< tab header="MacOS">}}
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cd $WORKSPACE
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wget https://dl.google.com/android/repository/android-ndk-r25b-darwin.zip
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unzip android-ndk-r25b-darwin
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mv android-ndk-r25b-darwin ~/Library/Android/android-ndk-r25b
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unzip android-ndk-r25b-darwin.zip
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mv android-ndk-r25b ~/Library/Android/android-ndk-r25b
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{{< /tab >}}
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{{< /tabpane >}}
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@@ -115,7 +126,6 @@ export PATH=$NDK_PATH/toolchains/llvm/prebuilt/linux-x86_64/bin/:$PATH
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{{< tab header="MacOS">}}
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export NDK_PATH=~/Library/Android/android-ndk-r25b
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export PATH=$PATH:$NDK_PATH/toolchains/llvm/prebuilt/darwin-x86_64/bin
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export PATH=$PATH:~/Library/Android/sdk/cmdline-tools/latest/bin
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{{< /tab >}}
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{{< /tabpane >}}
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content/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/3-converting-model.md

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@@ -87,7 +87,7 @@ You can use the provided script to convert the Conditioners submodule:
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python3 ./scripts/export_conditioners.py --model_config "$WORKSPACE/model_config.json" --ckpt_path "$WORKSPACE/model.ckpt"
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```
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After successful conversion, you now have a `tflite_conditioners` directory containing models with different precisions (e.g., float16, float32).
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After successful conversion, you now have a `conditioners_tflite` directory containing models with different precisions (e.g., float16, float32).
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You will be using the float32.tflite model for on-device inference.
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