Just working through the lesson1-pets notebook, which involves using resnet34, resnet50, and resnet18, all downloaded from the PyTorch site. There is mention of a model zoo on the PyTorch site, but the docs seem opaque on which models are available and how to access them.
Where can one find documentation for the models that are available and how to load them?
You should check out the fastai docs, where they have provided a link for the available pytorch models, and also extended that list.
For usage, if we are talking about an application related to vision, you can pass the desired model to a ConvLearner as a parameter: models.resnet18, models.densenet169 etc. as shown in the first lesson with models.resnet50/models.resnet34.
I am trying to use densenet in with create_cnn() but it gives me error how can i Use densnet in fasta.ai for transfer learning –
I get the following error in default pipeline-
arch = models.densenet169
AttributeError: module 'fastai.vision.models' has no attribute 'densenet169'
I have been playing with Cifar10 dataset for the last week or so with fastai-V1.
Remi’s pretrained models Squeeze-n-Excitation (se_resnet50) and fastai V1. I got my new year’s gift. Accuracy 0.9627 Cifar10-se_resnet.pdf (850.4 KB)