Transfer-learning with CondenseNet

[BDimitri]

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?

[ShichenLiu]

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.