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lite/examples/generative_ai/android/README.md

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@@ -6,18 +6,14 @@ Large language models (LLMs) are types of machine learning models that are creat
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This example shows you how to build an Android app with TensorFlow Lite to run a Keras LLM and provides suggestions for model optimization using quantizing techniques, which otherwise would require a much larger amount of memory and greater computational power to run.
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This example open sourced an Android app framework that any compatible TFLite LLMs can plug into. Here are two demos:
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* In Figure 1, we used a Keras GPT-2 model to perform text completion tasks on device.
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* In Figure 2, we converted a version of instruction-tuned [PaLM model](https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html) (1.5 billion parameters) to TFLite and executed through TFLite runtime.
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<p align="center">
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<img src="figures/autocomplete_fig1.gif" width="300">
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</p>
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Figure 1: Example of running the Keras GPT-2 model (converted from this Codelab) on device to perform text completion on Pixel 7. Demo shows the real latency with no speedup.
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<p align="center">
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<img src="figures/auto_complete_2.gif" width="300">
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</p>
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Figure 2: Example of running a version of [PaLM model](https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html) with 1.5 billion parameters. Demo is recorded on Pixel 7 Pro without playback speedup.
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* In Figure 1, we used a Keras GPT-2 model to perform text completion tasks on device.
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* In Figure 2, we converted a version of instruction-tuned [PaLM model](https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html) (1.5 billion parameters) to TFLite and executed through TFLite runtime.
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![Autocomplete with GPT-2](https://storage.googleapis.com/download.tensorflow.org/tflite/examples/autocomplete_fig1.gif){: width="300px"}
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<figcaption><b>Figure 1:</b>Example of running the Keras GPT-2 model (converted from this [Codelab](https://codelabs.developers.google.com/kerasnlp-tflite)) on device to perform text completion on Pixel 7. Demo shows the real latency with no speedup.</figcaption>
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![Autocomplete with PaLM](https://storage.googleapis.com/download.tensorflow.org/tflite/examples/autocomplete_fig2.gif){: width="300px"}
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<figcaption><b>Figure 2:</b>Example of running a version of [PaLM model](https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html) with 1.5 billion parameters. Demo is recorded on Pixel 7 Pro without playback speedup.</figcaption>
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