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 | 9.669 ms | 1 - 3 MB | FP16 | NPU |  [FFNet-122NS-LowRes.tflite](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 10.768 ms | 6 - 40 MB | FP16 | NPU |  [FFNet-122NS-LowRes.so](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 9.717 ms | 1 - 3 MB | FP16 | NPU |  [FFNet-122NS-LowRes.tflite](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 10.869 ms | 8 - 41 MB | FP16 | NPU |  [FFNet-122NS-LowRes.so](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.so) 
 
 
 ## Installation
@@ -96,16 +96,9 @@ python -m qai_hub_models.models.ffnet_122ns_lowres.export
 ```
 Profile Job summary of FFNet-122NS-LowRes
 --------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 9.66 ms
-Estimated Peak Memory Range: 0.00-3.85 MB
-Compute Units: NPU (216) | Total (216)
-
-Profile Job summary of FFNet-122NS-LowRes
---------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 10.82 ms
-Estimated Peak Memory Range: 6.04-36.75 MB
+Device: Snapdragon X Elite CRD (11)
+Estimated Inference Time: 17.55 ms
+Estimated Peak Memory Range: 6.01-6.01 MB
 Compute Units: NPU (348) | Total (348)