Upload README.md with huggingface_hub

README.md

@@ -33,8 +33,8 @@ 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 | 7.848 ms | 0 - 7 MB | FP16 | NPU |  [Yolo-v6.tflite](https://huggingface.co/qualcomm/Yolo-v6/blob/main/Yolo-v6.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 7.283 ms | 5 - 17 MB | FP16 | NPU |  [Yolo-v6.so](https://huggingface.co/qualcomm/Yolo-v6/blob/main/Yolo-v6.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 8.48 ms | 0 - 3 MB | FP16 | NPU |  [Yolo-v6.tflite](https://huggingface.co/qualcomm/Yolo-v6/blob/main/Yolo-v6.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 7.275 ms | 5 - 17 MB | FP16 | NPU |  [Yolo-v6.so](https://huggingface.co/qualcomm/Yolo-v6/blob/main/Yolo-v6.so) 
 
 
 ## Installation
@@ -94,16 +94,16 @@ python -m qai_hub_models.models.yolov6.export
 ```
 Profile Job summary of Yolo-v6
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 7.85 ms
-Estimated Peak Memory Range: 0.03-6.90 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 6.05 ms
+Estimated Peak Memory Range: 0.02-70.91 MB
 Compute Units: NPU (182) | Total (182)
 
 Profile Job summary of Yolo-v6
 --------------------------------------------------
-Device: Samsung Galaxy S23 Ultra (13)
-Estimated Inference Time: 7.28 ms
-Estimated Peak Memory Range: 4.70-16.65 MB
+Device: Samsung Galaxy S24 (14)
+Estimated Inference Time: 5.17 ms
+Estimated Peak Memory Range: 4.70-90.05 MB
 Compute Units: NPU (230) | Total (230)
 
 
@@ -223,7 +223,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of Yolo-v6 can be found
   [here](https://github.com/meituan/YOLOv6/blob/47625514e7480706a46ff3c0cd0252907ac12f22/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
 * [YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications](https://arxiv.org/abs/2209.02976)