Answers.Body: <p>You can find pretrained models on CIFAR-10 <a href="https://github.com/kuangliu/pytorch-cifar" rel="nofollow noreferrer">in this GitHub repository</a>.</p>
  <p>Also, for fun you can take any backbone trained on ImageNet from <a href="https://pytorch.org/vision/stable/models.html" rel="nofollow noreferrer">TorchVision models</a>.
  Just replace the classification part from the Linear layer, outputting 1000 classes to 10 or 100. Then you can freeze most of the layers of the network and fit just some bottom layers with the classification head (last <code>nn.Linear</code>).</p>
  <p>Modern papers often use CIFAR-10 for transfer learning and you can find the parameters in the paper or discussion on GitHub <a href="https://github.com/facebookresearch/deit/issues/45" rel="nofollow noreferrer">like here</a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-11-07T17:50:02.057Z
Answers.LastActivityDate: 2021-11-07T17:50:02.057Z
Answers.UserDisplayName: spiridon_the_sun_rotator
Body: <p>I'm looking for different models (specifically ResNet18/20, ResNet32/34, VGG16, MobileNet and SqueezeNet) and their parameters <strong>after</strong> training (i.e., <code>.pth</code> file) that were trained on <code>CIFAR-10</code> or <code>CIFAR-100</code>. I tried looking for them for hours and couldn't find anything. perhaps someone could refer me to a site which have trained models for <code>CIFAR-x</code>?</p>
  <p>Thank you.</p>
  
Tags: <models><weights>
Title: model and trained model parameters on CIFAR-10
UserDisplayName: user14092875
ThreadText: # model and trained model parameters on CIFAR-10
  
  (Asked by: username_0 on 2021-11-07)
  
  I'm looking for different models (specifically ResNet18/20, ResNet32/34, VGG16, MobileNet and SqueezeNet) and their parameters **after** training (i.e., `.pth` file) that were trained on `CIFAR-10` or `CIFAR-100`. I tried looking for them for hours and couldn't find anything. perhaps someone could refer me to a site which have trained models for `CIFAR-x`?
  
  Thank you.
  
  **Tags:** models, weights
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-11-07. Score: 1
  
  You can find pretrained models on CIFAR-10 [in this GitHub repository](https://github.com/kuangliu/pytorch-cifar).
  
  Also, for fun you can take any backbone trained on ImageNet from [TorchVision models](https://pytorch.org/vision/stable/models.html).
  Just replace the classification part from the Linear layer, outputting 1000 classes to 10 or 100. Then you can freeze most of the layers of the network and fit just some bottom layers with the classification head (last `nn.Linear`).
  
  Modern papers often use CIFAR-10 for transfer learning and you can find the parameters in the paper or discussion on GitHub [like here](https://github.com/facebookresearch/deit/issues/45).
  
  
  ---
  
  