qualcomm
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Inception-v3-Quantized

@@ -17,9 +17,12 @@ tags:
 # Inception-v3-Quantized: Optimized for Mobile Deployment
 ## Quantized Imagenet classifier and general purpose backbone
 InceptionNetV3 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases. This model is post-training quantized to int8 using samples from Google's open images dataset.
-This model is an implementation of Inception-v3-Quantized found [here]({source_repo}).
 This repository provides scripts to run Inception-v3-Quantized on Qualcomm® devices.
 More details on model performance across various devices, can be found
 [here](https://aihub.qualcomm.com/models/inception_v3_quantized).

 # Inception-v3-Quantized: Optimized for Mobile Deployment
 ## Quantized Imagenet classifier and general purpose backbone
 InceptionNetV3 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases. This model is post-training quantized to int8 using samples from Google's open images dataset.
+This model is an implementation of Posenet-Mobilenet found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/inception.py).
 This repository provides scripts to run Inception-v3-Quantized on Qualcomm® devices.
 More details on model performance across various devices, can be found
 [here](https://aihub.qualcomm.com/models/inception_v3_quantized).