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README.md
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@@ -35,8 +35,8 @@ More details on model performance across various devices, can be found
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| Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.
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```
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Profile Job summary of XLSR-Quantized
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Device:
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Estimated Inference Time: 0.
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Estimated Peak Memory Range: 0.06-
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Compute Units: NPU (
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```
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## Deploying compiled model to Android
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| Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.125 ms | 0 - 1 MB | INT8 | NPU | [XLSR-Quantized.tflite](https://huggingface.co/qualcomm/XLSR-Quantized/blob/main/XLSR-Quantized.tflite)
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.651 ms | 0 - 3 MB | INT8 | NPU | [XLSR-Quantized.so](https://huggingface.co/qualcomm/XLSR-Quantized/blob/main/XLSR-Quantized.so)
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```
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Profile Job summary of XLSR-Quantized
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--------------------------------------------------
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Device: Snapdragon X Elite CRD (11)
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Estimated Inference Time: 0.71 ms
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Estimated Peak Memory Range: 0.06-0.06 MB
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Compute Units: NPU (16) | Total (16)
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```
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## Run demo on a cloud-hosted device
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You can also run the demo on-device.
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```bash
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python -m qai_hub_models.models.xlsr_quantized.demo --on-device
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```
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**NOTE**: If you want running in a Jupyter Notebook or Google Colab like
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environment, please add the following to your cell (instead of the above).
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```
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%run -m qai_hub_models.models.xlsr_quantized.demo -- --on-device
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```
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## Deploying compiled model to Android
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