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README.md
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# Yolo-NAS-Quantized: Optimized for Mobile Deployment
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## Quantized real-time object detection optimized for mobile and edge
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YoloNAS is a machine learning model that predicts bounding boxes and classes of objects in an image. This model is post-training quantized to int8 using samples from the COCO dataset.
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This is based on the implementation of Yolo-NAS-Quantized found
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[here]({source_repo}). More details on model performance
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accross various devices, can be found [here](https://aihub.qualcomm.com/models/yolonas_quantized).
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# Yolo-NAS-Quantized: Optimized for Mobile Deployment
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## Quantized real-time object detection optimized for mobile and edge
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YoloNAS is a machine learning model that predicts bounding boxes and classes of objects in an image. This model is post-training quantized to int8 using samples from the COCO dataset.
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This model is an implementation of Posenet-Mobilenet found [here](https://github.com/Deci-AI/super-gradients).
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This is based on the implementation of Yolo-NAS-Quantized found
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[here]({source_repo}). More details on model performance
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accross various devices, can be found [here](https://aihub.qualcomm.com/models/yolonas_quantized).
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