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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 | 5.
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.
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Profile Job summary of YOLOv8-Detection
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Device: Snapdragon X Elite CRD (11)
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Estimated Inference Time: 5.
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Estimated Peak Memory Range: 4.70-4.70 MB
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Compute Units: NPU (285) | Total (285)
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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 | 5.199 ms | 0 - 3 MB | FP16 | NPU | [YOLOv8-Detection.tflite](https://huggingface.co/qualcomm/YOLOv8-Detection/blob/main/YOLOv8-Detection.tflite)
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| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 5.211 ms | 4 - 16 MB | FP16 | NPU | [YOLOv8-Detection.so](https://huggingface.co/qualcomm/YOLOv8-Detection/blob/main/YOLOv8-Detection.so)
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Profile Job summary of YOLOv8-Detection
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--------------------------------------------------
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Device: Snapdragon X Elite CRD (11)
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Estimated Inference Time: 5.38 ms
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Estimated Peak Memory Range: 4.70-4.70 MB
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Compute Units: NPU (285) | Total (285)
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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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