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README.md

@@ -33,10 +33,7 @@ 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 | 1.365 ms | 0 - 1 MB | FP16 | NPU |  [QuickSRNetSmall-Quantized.tflite](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.359 ms | 0 - 2 MB | INT8 | NPU |  [QuickSRNet_Small_Quantized.tflite](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNet_Small_Quantized.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 0.997 ms | 0 - 2 MB | FP16 | NPU |  [QuickSRNetSmall-Quantized.so](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.so) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 1.023 ms | 0 - 8 MB | INT8 | NPU |  [QuickSRNet_Small_Quantized.so](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNet_Small_Quantized.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 1.355 ms | 0 - 2 MB | INT8 | NPU |  [QuickSRNetSmall-Quantized.tflite](https://huggingface.co/qualcomm/QuickSRNetSmall-Quantized/blob/main/QuickSRNetSmall-Quantized.tflite) 
 
 
 ## Installation
@@ -96,31 +93,10 @@ python -m qai_hub_models.models.quicksrnetsmall_quantized.export
 ```
 Profile Job summary of QuickSRNetSmall-Quantized
 --------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 1.36 ms
-Estimated Peak Memory Range: 0.02-1.37 MB
-Compute Units: NPU (8),CPU (3) | Total (11)
-
-Profile Job summary of QuickSRNet_Small_Quantized
---------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 1.36 ms
-Estimated Peak Memory Range: 0.03-1.52 MB
-Compute Units: NPU (8),CPU (3) | Total (11)
-
-Profile Job summary of QuickSRNetSmall-Quantized
---------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 1.00 ms
-Estimated Peak Memory Range: 0.21-2.20 MB
-Compute Units: NPU (12) | Total (12)
-
-Profile Job summary of QuickSRNet_Small_Quantized
---------------------------------------------------
-Device: Samsung Galaxy S23 (13)
-Estimated Inference Time: 1.02 ms
-Estimated Peak Memory Range: 0.22-7.55 MB
-Compute Units: NPU (12) | Total (12)
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 1.10 ms
+Estimated Peak Memory Range: 0.02-19.27 MB
+Compute Units: NPU (10),CPU (3) | Total (13)
 
 
 ```
@@ -239,7 +215,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of QuickSRNetSmall-Quantized can be found
   [here](https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf).
-- The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf).
+- The license for the compiled assets for on-device deployment can be found [here]({deploy_license_url})
 
 ## References
 * [QuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster Inference on Mobile Platforms](https://arxiv.org/abs/2303.04336)