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add spiece model to models directory instead of workspace
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content/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/4-building-litert.md

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@@ -67,13 +67,11 @@ Once the Bazel configuration is complete, you can build LiteRT for your target p
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{{< tabpane code=true >}}
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{{< tab header="Android">}}
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```console
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bazel build -c opt --config android_arm64 //tensorflow/lite:libtensorflowlite.so \
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--define tflite_with_xnnpack=true \
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--define=xnn_enable_arm_i8mm=true \
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--define tflite_with_xnnpack_qs8=true \
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--define tflite_with_xnnpack_qu8=true
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```
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{{< /tab >}}
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{{< tab header="MacOS">}}
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bazel build -c opt --config macos //tensorflow/lite:libtensorflowlite.so \
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cmake --build .
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```
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Now that LiteRT and FlatBuffers are built, you're ready to compile and deploy the Stable Audio Open Small inference application on your Android device.
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Now that LiteRT and FlatBuffers are built, you're ready to compile and deploy the Stable Audio Open Small inference application on your Android or macOS device.
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content/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/6-creating-simple-program-for-macos.md

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@@ -33,14 +33,14 @@ After the example application builds successfully, a binary file named `audiogen
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A SentencePiece model is a type of subword tokenizer which is used by the audiogen application, you’ll need to download the *spiece.model* file from:
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```bash
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cd $WORKSPACE
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cd $LITERT_MODELS_PATH
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wget https://huggingface.co/google-t5/t5-base/resolve/main/spiece.model
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```
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Verify this model was downloaded to your `WORKSPACE`.
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```text
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ls $WORKSPACE/spiece.model
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ls $LITERT_MODELS_PATH/spiece.model
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```
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Copy the shared LiteRT dynamic library to the $LITERT_MODELS_PATH.
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Play around with the advice from [Download and test the model](../2-testing-model) section.
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```bash
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cd $WORKSPACE
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cd $WORKSPACE/ML-examples/kleidiai-examples/audiogen/app/
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./build/audiogen $LITERT_MODELS_PATH "warm arpeggios on house beats 120BPM with drums effect" 4
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```
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