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Upload README.md with huggingface_hub

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  # MobileNet-v3-Large: Optimized for Mobile Deployment
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  ## Imagenet classifier and general purpose backbone
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- MobileNetV3Large 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.
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  This model is an implementation of MobileNet-v3-Large found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv3.py).
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  This repository provides scripts to run MobileNet-v3-Large on Qualcomm® devices.
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  | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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  | ---|---|---|---|---|---|---|---|
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- | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 0.6 ms | 0 - 17 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite)
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  ## Installation
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  ```
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  Profile Job summary of MobileNet-v3-Large
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  --------------------------------------------------
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- Device: Samsung Galaxy S23 Ultra (13)
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- Estimated Inference Time: 0.60 ms
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- Estimated Peak Memory Range: 0.03-16.92 MB
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  Compute Units: NPU (134) | Total (134)
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  ## License
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  - The license for the original implementation of MobileNet-v3-Large can be found
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  [here](https://github.com/pytorch/vision/blob/main/LICENSE).
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- - 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).
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  ## References
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  * [Searching for MobileNetV3](https://arxiv.org/abs/1905.02244)
 
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  # MobileNet-v3-Large: Optimized for Mobile Deployment
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  ## Imagenet classifier and general purpose backbone
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+ MobileNet-v3-Large 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.
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  This model is an implementation of MobileNet-v3-Large found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv3.py).
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  This repository provides scripts to run MobileNet-v3-Large on Qualcomm® devices.
 
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  | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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  | ---|---|---|---|---|---|---|---|
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+ | Samsung Galaxy S23 Ultra (Android 13) | Snapdragon® 8 Gen 2 | TFLite | 0.603 ms | 0 - 2 MB | FP16 | NPU | [MobileNet-v3-Large.tflite](https://huggingface.co/qualcomm/MobileNet-v3-Large/blob/main/MobileNet-v3-Large.tflite)
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  ## Installation
 
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  ```
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  Profile Job summary of MobileNet-v3-Large
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  --------------------------------------------------
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+ Device: Samsung Galaxy S24 (14)
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+ Estimated Inference Time: 0.43 ms
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+ Estimated Peak Memory Range: 0.01-57.22 MB
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  Compute Units: NPU (134) | Total (134)
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  ## License
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  - The license for the original implementation of MobileNet-v3-Large can be found
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  [here](https://github.com/pytorch/vision/blob/main/LICENSE).
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+ - The license for the compiled assets for on-device deployment can be found [here]({deploy_license_url})
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  ## References
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  * [Searching for MobileNetV3](https://arxiv.org/abs/1905.02244)