{"library":"pretrainedmodels","title":"Pretrained models for Pytorch","description":"A library providing pretrained models for PyTorch, including architectures like ResNet, DenseNet, Inception, and more. Version 0.7.4 is the latest release, though the project is in maintenance mode with infrequent updates. It is commonly used for transfer learning and feature extraction, but users should prefer torchvision's model zoo for active support.","language":"python","status":"maintenance","last_verified":"Mon Apr 27","install":{"commands":["pip install pretrainedmodels"],"cli":null},"imports":["import pretrainedmodels","from pretrainedmodels import models"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import torch\nimport pretrainedmodels\n\nmodel = pretrainedmodels.__dict__['resnet101'](pretrained='imagenet')\nmodel.eval()\nprint(model)\n\n# Example inference\nfrom pretrainedmodels import utils\nimport torchvision.transforms as transforms\n\ntf = utils.TransformImage(model)\ninput_tensor = torch.randn(1, 3, 224, 224)\nout = model(input_tensor)\nprint(out.shape)","lang":"python","description":"Load a pretrained ResNet-101 model and run inference.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}