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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 | 2.822 ms | 0 - 2 MB | FP16 | NPU |  [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 2.908 ms | 0 - 20 MB | FP16 | NPU |  [HRNetPose.so](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 2.824 ms | 0 - 3 MB | FP16 | NPU |  [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 2.922 ms | 0 - 17 MB | FP16 | NPU |  [HRNetPose.so](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.so) 
 
 
 
@@ -98,8 +98,8 @@ python -m qai_hub_models.models.hrnet_pose.export
 Profile Job summary of HRNetPose
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 3.13 ms
-Estimated Peak Memory Range: 0.86-0.86 MB
+Estimated Inference Time: 2.89 ms
+Estimated Peak Memory Range: 0.56-0.56 MB
 Compute Units: NPU (747) | Total (747)
 
 
@@ -125,7 +125,6 @@ from qai_hub_models.models.hrnet_pose import Model
 
 # Load the model
 torch_model = Model.from_pretrained()
-torch_model.eval()
 
 # Device
 device = hub.Device("Samsung Galaxy S23")