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https://github.com/huggingface/pytorch-image-models.git
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Add weights for test models
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1a05ed29a1
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@ -2352,8 +2352,8 @@ default_cfgs = generate_default_cfgs({
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input_size=(3, 256, 256), pool_size=(8, 8),
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input_size=(3, 256, 256), pool_size=(8, 8),
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),
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),
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'test_byobnet.untrained': _cfgr(
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'test_byobnet.r160_in1k': _cfgr(
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# hf_hub_id='timm/',
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hf_hub_id='timm/',
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first_conv='stem.conv',
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first_conv='stem.conv',
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input_size=(3, 160, 160), crop_pct=0.875, pool_size=(5, 5),
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input_size=(3, 160, 160), crop_pct=0.875, pool_size=(5, 5),
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),
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),
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@ -1756,8 +1756,8 @@ default_cfgs = generate_default_cfgs({
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#hf_hub_id='timm/',
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#hf_hub_id='timm/',
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input_size=(3, 224, 224), crop_pct=0.9),
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input_size=(3, 224, 224), crop_pct=0.9),
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"test_efficientnet.untrained": _cfg(
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"test_efficientnet.r160_in1k": _cfg(
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# hf_hub_id='timm/'
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hf_hub_id='timm/',
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input_size=(3, 160, 160), pool_size=(5, 5)),
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input_size=(3, 160, 160), pool_size=(5, 5)),
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})
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})
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@ -1990,7 +1990,8 @@ default_cfgs = {
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'vit_so150m_patch16_reg4_map_256.untrained': _cfg(
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'vit_so150m_patch16_reg4_map_256.untrained': _cfg(
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input_size=(3, 256, 256)),
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input_size=(3, 256, 256)),
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'test_vit.untrained': _cfg(
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'test_vit.r160_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 160, 160), crop_pct=0.875),
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input_size=(3, 160, 160), crop_pct=0.875),
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}
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}
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