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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 | 48.23 ms | 4 - 7 MB | FP16 | NPU |  [SAMDecoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMDecoder.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 12009.97 ms | 2597 - 2601 MB | FP32 | CPU |  [SAMEncoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMEncoder.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 48.549 ms | 4 - 13 MB | FP16 | NPU |  [SAMDecoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMDecoder.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 11689.749 ms | 2538 - 2547 MB | FP32 | CPU |  [SAMEncoder.tflite](https://huggingface.co/qualcomm/Segment-Anything-Model/blob/main/SAMEncoder.tflite) 
 
 
 
@@ -98,17 +98,17 @@ python -m qai_hub_models.models.sam.export
 ```
 Profile Job summary of SAMDecoder
 --------------------------------------------------
-Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 48.06 ms
-Estimated Peak Memory Range: 3.82-11.95 MB
-Compute Units: NPU (340) | Total (340)
+Device: SA8775 (Proxy) (13)
+Estimated Inference Time: 47.98 ms
+Estimated Peak Memory Range: 3.85-6.72 MB
+Compute Units: NPU (341) | Total (341)
 
 Profile Job summary of SAMEncoder
 --------------------------------------------------
 Device: QCS8550 (Proxy) (12)
-Estimated Inference Time: 11285.66 ms
-Estimated Peak Memory Range: 2519.75-2523.24 MB
-Compute Units: GPU (37),CPU (771) | Total (808)
+Estimated Inference Time: 11668.45 ms
+Estimated Peak Memory Range: 2593.73-2598.27 MB
+Compute Units: GPU (37),CPU (783) | Total (820)
 
 
 ```
@@ -133,7 +133,6 @@ from qai_hub_models.models.sam import Model
 
 # Load the model
 torch_model = Model.from_pretrained()
-torch_model.eval()
 
 # Device
 device = hub.Device("Samsung Galaxy S23")