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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 | 346.284 ms | 104 - 107 MB | FP32 | CPU |  [DETR-ResNet50.tflite](https://huggingface.co/qualcomm/DETR-ResNet50/blob/main/DETR-ResNet50.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 365.312 ms | 104 - 424 MB | FP32 | CPU |  [DETR-ResNet50.tflite](https://huggingface.co/qualcomm/DETR-ResNet50/blob/main/DETR-ResNet50.tflite) 
 
 
 ## Installation
@@ -95,9 +95,9 @@ python -m qai_hub_models.models.detr_resnet50.export
 ```
 Profile Job summary of DETR-ResNet50
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 346.28 ms
-Estimated Peak Memory Range: 104.07-106.82 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 287.30 ms
+Estimated Peak Memory Range: 103.19-187.82 MB
 Compute Units: CPU (889) | Total (889)
 
 
@@ -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-ResNet50 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)