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- lightweight GAN trained on glid-3 orbs for demo I'm working on.
 
 
 
 
 
 
 
 
 
 
 
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  Training notebook: https://colab.research.google.com/drive/16o1TdrxnQ54Msbr813XfPVsnEt2QTRAa?usp=sharing
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@@ -6,9 +17,9 @@ Inference notebook: https://colab.research.google.com/drive/1e7dR2dptM8F1xhRcyy-
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  Please credit if you use this, and feedback on the code is welcomed :)
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- Demo:
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- from lightweight_gan import Generator
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  import torch
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  from matplotlib import pyplot as plt
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  from huggingface_hub import PyTorchModelHubMixin
@@ -31,4 +42,4 @@ ims = gan_new(torch.randn(n_rows**2, 256)).clamp_(0., 1.)
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  fig, axs = plt.subplots(n_rows, n_rows, figsize=(9, 9))
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  for i, ax in enumerate(axs.flatten()):
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  ax.imshow(ims[i].permute(1, 2, 0).detach().cpu().numpy())
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- plt.tight_layout()
 
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+ ---
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+ language: en
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+ tags:
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+ - lightweightgan
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+ license: apache-2.0
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+ datasets:
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+ - johnowhitaker/glid3_orbs
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+ ---
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+
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+ # orbgan
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+
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+ lightweight GAN trained on my glid-3 orbs for demo I'm working on.
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  Training notebook: https://colab.research.google.com/drive/16o1TdrxnQ54Msbr813XfPVsnEt2QTRAa?usp=sharing
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  Please credit if you use this, and feedback on the code is welcomed :)
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+ ## Demo:
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+ ```from lightweight_gan import Generator
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  import torch
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  from matplotlib import pyplot as plt
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  from huggingface_hub import PyTorchModelHubMixin
 
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  fig, axs = plt.subplots(n_rows, n_rows, figsize=(9, 9))
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  for i, ax in enumerate(axs.flatten()):
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  ax.imshow(ims[i].permute(1, 2, 0).detach().cpu().numpy())
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+ plt.tight_layout()```