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README.md

@@ -36,6 +36,8 @@ More details on model performance across various devices, can be found
   - Model size: 1.4GB
 
 
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 | 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 | QNN Binary | 11.394 ms | 0 - 74 MB | UINT16 | NPU |  [TextEncoder_Quantized.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/TextEncoder_Quantized.bin) 
@@ -44,6 +46,7 @@ More details on model performance across various devices, can be found
 | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | QNN Binary | 100.33 ms | 2 - 68 MB | UINT16 | NPU |  [ControlNet_Quantized.bin](https://huggingface.co/qualcomm/ControlNet/blob/main/ControlNet_Quantized.bin) 
 
 
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 ## Installation
 
 This model can be installed as a Python package via pip.
@@ -130,9 +133,11 @@ Compute Units: NPU (2406) | Total (2406)
 
 
 ```
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 ## How does this work?
 
-This [export script](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/ControlNet/export.py)
+This [export script](https://aihub.qualcomm.com/models/controlnet_quantized/qai_hub_models/models/ControlNet/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:
 
@@ -231,6 +236,7 @@ AI Hub. [Sign up for access](https://myaccount.qualcomm.com/signup).
 
 
 
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 ## Deploying compiled model to Android
 
 
@@ -252,7 +258,7 @@ Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)
 ## License
 - The license for the original implementation of ControlNet can be found
   [here](https://github.com/lllyasviel/ControlNet/blob/main/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://github.com/lllyasviel/ControlNet/blob/main/LICENSE)
 
 ## References
 * [Adding Conditional Control to Text-to-Image Diffusion Models](https://arxiv.org/abs/2302.05543)