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README.md

@@ -36,8 +36,8 @@ 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 | 9.538 ms | 0 - 2 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 | 10.684 ms | 7 - 22 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 | 6.446 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 | 6.982 ms | 6 - 31 MB | FP16 | NPU |  [FFNet-122NS-LowRes.so](https://huggingface.co/qualcomm/FFNet-122NS-LowRes/blob/main/FFNet-122NS-LowRes.so) 
 
 
 
@@ -100,7 +100,7 @@ python -m qai_hub_models.models.ffnet_122ns_lowres.export
 Profile Job summary of FFNet-122NS-LowRes
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 17.38 ms
+Estimated Inference Time: 6.31 ms
 Estimated Peak Memory Range: 6.01-6.01 MB
 Compute Units: NPU (348) | Total (348)
 
@@ -127,7 +127,6 @@ from qai_hub_models.models.ffnet_122ns_lowres import Model
 
 # Load the model
 torch_model = Model.from_pretrained()
-torch_model.eval()
 
 # Device
 device = hub.Device("Samsung Galaxy S23")