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README.md
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@@ -36,8 +36,8 @@ 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 | 13.
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 12.
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Profile Job summary of DeepLabV3-Plus-MobileNet
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Device: Snapdragon X Elite CRD (11)
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Estimated Inference Time:
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Estimated Peak Memory Range: 3.02-3.02 MB
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Compute Units: NPU (124) | Total (124)
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# Load the model
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torch_model = Model.from_pretrained()
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torch_model.eval()
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# Device
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device = hub.Device("Samsung Galaxy S23")
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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 | 13.087 ms | 18 - 20 MB | FP16 | NPU | [DeepLabV3-Plus-MobileNet.tflite](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet/blob/main/DeepLabV3-Plus-MobileNet.tflite)
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 12.849 ms | 3 - 17 MB | FP16 | NPU | [DeepLabV3-Plus-MobileNet.so](https://huggingface.co/qualcomm/DeepLabV3-Plus-MobileNet/blob/main/DeepLabV3-Plus-MobileNet.so)
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Profile Job summary of DeepLabV3-Plus-MobileNet
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--------------------------------------------------
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Device: Snapdragon X Elite CRD (11)
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Estimated Inference Time: 12.86 ms
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Estimated Peak Memory Range: 3.02-3.02 MB
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Compute Units: NPU (124) | Total (124)
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# Load the model
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torch_model = Model.from_pretrained()
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# Device
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device = hub.Device("Samsung Galaxy S23")
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