Lupin1998
commited on
Commit
•
f1ea797
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Parent(s):
5e40b1d
fix moganet_tiny_224_in1k
Browse files
README.md
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@@ -17,7 +17,7 @@ widget:
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example_title: Tiger
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---
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# Model card for
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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('
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model = model.eval()
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# get model specific transforms (normalization, resize)
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@@ -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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'
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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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)
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