{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"}],"enrichment":{"capability":"Loads and runs pretrained EfficientNet image classification models in PyTorch, supporting both standard and adversarially-trained variants for inference and feature extraction.","skillfed_tags":["deep-learning","computer-vision","transfer-learning"],"use_cases":["Load a pretrained EfficientNet model for image classification on new images without retraining.","Extract learned features from intermediate layers for use in downstream tasks or custom classifiers.","Fine-tune an EfficientNet on a custom dataset by loading a pretrained model with a different number of output classes.","Benchmark or compare EfficientNet accuracy against other architectures on ImageNet or custom validation sets.","Export a trained EfficientNet to ONNX format for deployment in production environments outside PyTorch."],"what_it_does":"EfficientNet PyTorch is a PyTorch reimplementation of the EfficientNet family of convolutional neural networks, which are designed to achieve high image classification accuracy with fewer parameters and lower computational cost than previous models. The package provides pretrained models (EfficientNet-B0 through B8) that can be loaded directly for inference or adapted for transfer learning on custom datasets.\n\nThe package supports both standard ImageNet-pretrained weights and adversarially-trained (advprop) variants, with different preprocessing requirements for each. You can use models for classification, feature extraction, or export to ONNX format. However, the package has been abandoned since April 2021 and receives no maintenance, meaning it may not work reliably with modern PyTorch versions or Python environments.","worth_installing":"No, unless you are locked into an older PyTorch environment. The package is abandoned (last release April 2021, no commits since), so it will not receive security updates, compatibility fixes, or support for modern PyTorch versions. If you need EfficientNet models, consider using PyTorch's built-in torchvision.models or the official TensorFlow implementation instead."},"id":"efficientnet-pytorch","links":{"html":"https://skillfed.io/packages/efficientnet-pytorch","md":"https://skillfed.io/packages/efficientnet-pytorch.md","pypi":"https://pypi.org/project/efficientnet-pytorch/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2021-04-15","license_spdx":null,"license_treatment":"permissive","name":"efficientnet-pytorch","python_support":"supports_current","summary":"EfficientNet implemented in PyTorch."},"popularity":{"monthly_downloads":162491,"position":10599,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.7.1"}