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Upload README.md with huggingface_hub

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@@ -38,8 +38,8 @@ 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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  | ---|---|---|---|---|---|---|---|
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- | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 4.868 ms | 0 - 2 MB | FP16 | NPU | [WideResNet50.tflite](https://huggingface.co/qualcomm/WideResNet50/blob/main/WideResNet50.tflite)
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- | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.652 ms | 1 - 238 MB | FP16 | NPU | [WideResNet50.so](https://huggingface.co/qualcomm/WideResNet50/blob/main/WideResNet50.so)
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@@ -101,7 +101,7 @@ python -m qai_hub_models.models.wideresnet50.export
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  Profile Job summary of WideResNet50
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  --------------------------------------------------
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  Device: Snapdragon X Elite CRD (11)
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- Estimated Inference Time: 5.84 ms
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  Estimated Peak Memory Range: 0.57-0.57 MB
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  Compute Units: NPU (126) | Total (126)
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@@ -128,7 +128,6 @@ from qai_hub_models.models.wideresnet50 import Model
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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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  | ---|---|---|---|---|---|---|---|
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+ | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 4.893 ms | 0 - 2 MB | FP16 | NPU | [WideResNet50.tflite](https://huggingface.co/qualcomm/WideResNet50/blob/main/WideResNet50.tflite)
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+ | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.681 ms | 1 - 339 MB | FP16 | NPU | [WideResNet50.so](https://huggingface.co/qualcomm/WideResNet50/blob/main/WideResNet50.so)
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  Profile Job summary of WideResNet50
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  --------------------------------------------------
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  Device: Snapdragon X Elite CRD (11)
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+ Estimated Inference Time: 4.66 ms
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  Estimated Peak Memory Range: 0.57-0.57 MB
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  Compute Units: NPU (126) | Total (126)
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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")