EfficientNet (b0 model) EfficientNet model trained on ImageNet 1k at resolution 224x224. It was introduced in the paper EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks by Mingxing Tan and Quoc V. Le, and first released in this repository. Disclaimer: The team releasing EfficientNet did not write a model card for this model so this model card has been written by the Hugging Face team. Model description EfficientNet is a mobile friendly pure convolutional model (ConvNet) that proposes a new scaling method that uniformly scales all dimensions of depth/width/resolution using a simple yet highly effective compound coefficient. Intended uses & limitations You can use the raw model for image classification. See the model hub to look for fine tuned versions on a task that interests you. How to use Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes: For more code examples, we refer to the documentation. BibTeX entry and citation info
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