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Add remaining sbb vit betwixt/mediumd fine-tunes
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timm/models/vision_transformer.py

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@@ -1964,6 +1964,9 @@ def _cfg(url: str = '', **kwargs) -> Dict[str, Any]:
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hf_hub_id='timm/',
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num_classes=11821,
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input_size=(3, 256, 256), crop_pct=0.95),
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'vit_mediumd_patch16_reg4_gap_256.sbb2_e200_in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 256, 256), crop_pct=0.95),
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'vit_mediumd_patch16_reg4_gap_256.sbb_in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 256, 256), crop_pct=0.95),
@@ -1975,9 +1978,15 @@ def _cfg(url: str = '', **kwargs) -> Dict[str, Any]:
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hf_hub_id='timm/',
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num_classes=11821,
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input_size=(3, 256, 256), crop_pct=0.95),
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'vit_mediumd_patch16_reg4_gap_384.sbb2_e200_in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 384, 384), crop_pct=1.0),
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'vit_betwixt_patch16_reg1_gap_256.sbb_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 256, 256), crop_pct=0.95),
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'vit_betwixt_patch16_reg4_gap_256.sbb2_e200_in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 256, 256), crop_pct=0.95),
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'vit_betwixt_patch16_reg4_gap_256.sbb_in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 256, 256), crop_pct=0.95),
@@ -1992,6 +2001,9 @@ def _cfg(url: str = '', **kwargs) -> Dict[str, Any]:
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hf_hub_id='timm/',
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num_classes=11821,
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input_size=(3, 256, 256), crop_pct=0.95),
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'vit_betwixt_patch16_reg4_gap_384.sbb2_e200_in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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input_size=(3, 384, 384), crop_pct=1.0),
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'vit_base_patch16_reg4_gap_256.untrained': _cfg(
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input_size=(3, 256, 256)),
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@@ -3118,6 +3130,17 @@ def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> Visi
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return model
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@register_model
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def vit_mediumd_patch16_reg4_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
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model_args = dict(
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patch_size=16, embed_dim=512, depth=20, num_heads=8, init_values=1e-5,
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class_token=False, no_embed_class=True, reg_tokens=4, global_pool='avg',
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)
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model = _create_vision_transformer(
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'vit_mediumd_patch16_reg4_gap_384', pretrained=pretrained, **dict(model_args, **kwargs))
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return model
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@register_model
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def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
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model_args = dict(
@@ -3140,6 +3163,17 @@ def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> Visi
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return model
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@register_model
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def vit_betwixt_patch16_reg4_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
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model_args = dict(
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patch_size=16, embed_dim=640, depth=12, num_heads=10, init_values=1e-5,
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class_token=False, no_embed_class=True, reg_tokens=4, global_pool='avg',
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)
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model = _create_vision_transformer(
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'vit_betwixt_patch16_reg4_gap_384', pretrained=pretrained, **dict(model_args, **kwargs))
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return model
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@register_model
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def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
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model_args = dict(

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