Most of torchvision convolutional networks could work with different image sizes, except for perhaps this:

Important: In contrast to the other models the inception_v3 expects tensors with a size of N x 3 x 299 x 299, so ensure your images are sized accordingly.

This note is from torchvision.models documentation 99. So, to be save I would at least check for documentation.
On the other hand not all sizes a meaningful for the networks of different depths, because they could convolve images to much or to less thus getting not so optimal receptive fields.
Given that, I can defenetly recommend this github repo 29. There is a bunch of pretrained models and you can check the image size used for training models in the results spreadsheets here 23 .
Hope it helps!