CondenseNet

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Hello, I am getting good accuracy with CondenseNet on my dataset when training from scratch, but I feel like I could boost the results if I could train from a checkpoint pretrained on ImageNet. You offer the converted checkpoints on ImageNet, but my understanding of the situation is that I can't use that for transfer learning because its missing some dicts like the optimizer. Since I am new to pytorch I feel like I am missing something. Is it possible to train from the converted checkpoint? If no, would it be possible to upload the unconverted model?

Sorry for being late. As far as I know, you don't need the state dict of optimizer to do transfer learning. Just load the converted weight and train should be fine.