Upload README.md with huggingface_hub

README.md

@@ -34,8 +34,8 @@ 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 | 155.616 ms | 6 - 219 MB | FP16 | NPU |  [Unet-Segmentation.tflite](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 150.609 ms | 9 - 32 MB | FP16 | NPU |  [Unet-Segmentation.so](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 161.691 ms | 0 - 226 MB | FP16 | NPU |  [Unet-Segmentation.tflite](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 149.965 ms | 10 - 29 MB | FP16 | NPU |  [Unet-Segmentation.so](https://huggingface.co/qualcomm/Unet-Segmentation/blob/main/Unet-Segmentation.so) 
 
 
 ## Installation
@@ -95,16 +95,9 @@ python -m qai_hub_models.models.unet_segmentation.export
 ```
 Profile Job summary of Unet-Segmentation
 --------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 160.84 ms
-Estimated Peak Memory Range: 0.31-226.50 MB
-Compute Units: NPU (31) | Total (31)
-
-Profile Job summary of Unet-Segmentation
---------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 150.01 ms
-Estimated Peak Memory Range: 9.44-32.58 MB
+Device: Snapdragon X Elite CRD (11)
+Estimated Inference Time: 190.74 ms
+Estimated Peak Memory Range: 9.39-9.39 MB
 Compute Units: NPU (51) | Total (51)