Upload README.md with huggingface_hub

README.md

@@ -35,8 +35,8 @@ More details on model performance across various devices, can be found
 
 | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
 | ---|---|---|---|---|---|---|---|
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.122 ms | 2 - 3 MB | INT8 | NPU |  [QuickSRNetSmall-Quantized.tflite](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.663 ms | 0 - 10 MB | INT8 | NPU |  [QuickSRNetSmall-Quantized.so](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.122 ms | 0 - 74 MB | INT8 | NPU |  [QuickSRNetSmall-Quantized.tflite](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.469 ms | 0 - 19 MB | INT8 | NPU |  [QuickSRNetSmall-Quantized.so](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.so) 
 
 
 
@@ -98,10 +98,10 @@ python -m qai_hub_models.models.quicksrnetsmall_quantized.export
 ```
 Profile Job summary of QuickSRNetSmall-Quantized
 --------------------------------------------------
-Device: SA8255 (Proxy) (13)
-Estimated Inference Time: 0.68 ms
-Estimated Peak Memory Range: 0.02-64.42 MB
-Compute Units: NPU (8) | Total (8)
+Device: Snapdragon X Elite CRD (11)
+Estimated Inference Time: 0.56 ms
+Estimated Peak Memory Range: 0.06-0.06 MB
+Compute Units: NPU (7) | Total (7)
 
 
 ```