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README.md

@@ -30,10 +30,13 @@ More details on model performance across various devices, can be found
   - Model size: 4.66 MB
 
 
+
+
 | 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 | 7.495 ms | 15 - 17 MB | FP16 | NPU |  [Real-ESRGAN-General-x4v3.tflite](https://huggingface.co/qualcomm/Real-ESRGAN-General-x4v3/blob/main/Real-ESRGAN-General-x4v3.tflite) 
-| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 6.301 ms | 0 - 108 MB | FP16 | NPU |  [Real-ESRGAN-General-x4v3.so](https://huggingface.co/qualcomm/Real-ESRGAN-General-x4v3/blob/main/Real-ESRGAN-General-x4v3.so) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 7.261 ms | 17 - 24 MB | FP16 | NPU |  [Real-ESRGAN-General-x4v3.tflite](https://huggingface.co/qualcomm/Real-ESRGAN-General-x4v3/blob/main/Real-ESRGAN-General-x4v3.tflite) 
+| Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Model Library | 6.295 ms | 0 - 5 MB | FP16 | NPU |  [Real-ESRGAN-General-x4v3.so](https://huggingface.co/qualcomm/Real-ESRGAN-General-x4v3/blob/main/Real-ESRGAN-General-x4v3.so) 
+
 
 
 ## Installation
@@ -95,15 +98,17 @@ python -m qai_hub_models.models.real_esrgan_general_x4v3.export
 Profile Job summary of Real-ESRGAN-General-x4v3
 --------------------------------------------------
 Device: Snapdragon X Elite CRD (11)
-Estimated Inference Time: 9.19 ms
-Estimated Peak Memory Range: 0.22-0.22 MB
+Estimated Inference Time: 8.67 ms
+Estimated Peak Memory Range: 0.20-0.20 MB
 Compute Units: NPU (72) | Total (72)
 
 
 ```
+
+
 ## How does this work?
 
-This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/Real-ESRGAN-General-x4v3/export.py)
+This [export script](https://aihub.qualcomm.com/models/real_esrgan_general_x4v3/qai_hub_models/models/Real-ESRGAN-General-x4v3/export.py)
 leverages [Qualcomm® AI Hub](https://aihub.qualcomm.com/) to optimize, validate, and deploy this model
 on-device. Lets go through each step below in detail:
 
@@ -180,6 +185,7 @@ spot check the output with expected output.
 AI Hub. [Sign up for access](https://myaccount.qualcomm.com/signup).
 
 
+
 ## Run demo on a cloud-hosted device
 
 You can also run the demo on-device.
@@ -216,7 +222,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of Real-ESRGAN-General-x4v3 can be found
   [here](https://github.com/xinntao/Real-ESRGAN/blob/master/LICENSE).
-- The license for the compiled assets for on-device deployment can be found [here]({deploy_license_url})
+- 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)
 
 ## References
 * [Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data](https://arxiv.org/abs/2107.10833)