Image Classification
timm
English
vision
Lupin1998 commited on
Commit
f1ea797
1 Parent(s): 5e40b1d

fix moganet_tiny_224_in1k

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Files changed (1) hide show
  1. README.md +3 -3
README.md CHANGED
@@ -17,7 +17,7 @@ widget:
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  example_title: Tiger
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  ---
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- # Model card for moganet_xtiny_256_in1k
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  MogaNet a new family of efficient ConvNets with preferable parameter-performance trade-offs, which is trained on ImageNet-1k (1 million images, 1,000 classes). It was first introduced in the paper [MogaNet](https://arxiv.org/abs/2211.03295) and released in [Westlake/MogaNet](https://github.com/Westlake-AI/MogaNet) and [Westlake/openmixup](https://github.com/Westlake-AI/openmixup).
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@@ -45,7 +45,7 @@ import models
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  img = Image.open(
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  urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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- model = timm.create_model('moganet_xtiny_1k_sz256', pretrained=True)
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  model = model.eval()
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  # get model specific transforms (normalization, resize)
@@ -67,7 +67,7 @@ img = Image.open(
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  urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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  model = timm.create_model(
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- 'moganet_xtiny_1k_sz256',
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  pretrained=True,
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  fork_feat=True,
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  )
 
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  example_title: Tiger
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  ---
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+ # Model card for moganet_tiny_224_in1k
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  MogaNet a new family of efficient ConvNets with preferable parameter-performance trade-offs, which is trained on ImageNet-1k (1 million images, 1,000 classes). It was first introduced in the paper [MogaNet](https://arxiv.org/abs/2211.03295) and released in [Westlake/MogaNet](https://github.com/Westlake-AI/MogaNet) and [Westlake/openmixup](https://github.com/Westlake-AI/openmixup).
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  img = Image.open(
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  urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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+ model = timm.create_model('moganet_tiny_1k', pretrained=True)
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  model = model.eval()
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  # get model specific transforms (normalization, resize)
 
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  urlopen('https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'))
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  model = timm.create_model(
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+ 'moganet_tiny_1k',
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  pretrained=True,
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  fork_feat=True,
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  )