#MobileNetV3

This repository provides a generic implementation of various compute-efficient models such as EfficientNet, MixNet, and MobileNetV3, rooted in MobileNet V1/V2 architecture blocks. Note: The repository is no longer maintained; consider the 'timm' library for more up-to-date features. Key updates have brought new MobileNet-V2 models with advanced parameters, improved EfficientNet variants with NoisyStudent and AdvProp optimizations, and refined ONNX/Caffe2 export capabilities, enhancing AI model validation and deployment with pretrained weights.

This open-source project provides a wide range of image classification backbones compatible with Python 3.6+ and PyTorch 1.7.1+. Explore models like MobileViT and EfficientNetV2, featuring pre-trained weights for seamless integration. Tutorials on setup, data handling, and evaluation assist in enhancing training efficacy and stability. Suitable for developers aiming for adaptable and strong frameworks in AI-powered image assessment.