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README.md

@@ -34,7 +34,7 @@ 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 | 640.294 ms | 102 - 106 MB | FP32 | CPU |  [DETR-ResNet101.tflite](https://huggingface.co/qualcomm/DETR-ResNet101/blob/main/DETR-ResNet101.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 563.957 ms | 98 - 107 MB | FP32 | CPU |  [DETR-ResNet101.tflite](https://huggingface.co/qualcomm/DETR-ResNet101/blob/main/DETR-ResNet101.tflite) 
 
 
 ## Installation
@@ -95,9 +95,9 @@ python -m qai_hub_models.models.detr_resnet101.export
 ```
 Profile Job summary of DETR-ResNet101
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 640.29 ms
-Estimated Peak Memory Range: 102.30-106.38 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 489.87 ms
+Estimated Peak Memory Range: 104.88-254.46 MB
 Compute Units: CPU (957) | Total (957)
 
 
@@ -217,7 +217,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of DETR-ResNet101 can be found
   [here](https://github.com/facebookresearch/detr/blob/main/LICENSE).
-- 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
 * [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872)