Remove duplicate so400m/16 @ 256 model def
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dc5c7989ae
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25de6b4ee1
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@ -3499,18 +3499,6 @@ def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> Vis
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return model
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@register_model
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def vit_so400m_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
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""" A SigLIP variant of ViT with global average pooling (GAP) instead of attention pooling (MAP)."""
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model_args = dict(
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patch_size=16, embed_dim=1152, depth=27, num_heads=16, mlp_ratio=3.7362,
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class_token=False, global_pool='avg', fc_norm=False,
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)
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model = _create_vision_transformer(
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'vit_so400m_patch16_siglip_gap_256', pretrained=pretrained, **dict(model_args, **kwargs))
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return model
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@register_model
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def vit_so400m_patch14_siglip_gap_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
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""" A SigLIP variant of ViT with global average pooling (GAP) instead of attention pooling (MAP)."""
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@ -3561,9 +3549,10 @@ def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> Vis
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@register_model
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def vit_so400m_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
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""" A SigLIP variant of ViT with global average pooling (GAP) instead of attention pooling (MAP)."""
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model_args = dict(
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patch_size=16, embed_dim=1152, depth=27, num_heads=16, mlp_ratio=3.7362, class_token=False,
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global_pool='avg', fc_norm=False, act_layer='gelu_tanh'
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patch_size=16, embed_dim=1152, depth=27, num_heads=16, mlp_ratio=3.7362,
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class_token=False, global_pool='avg', fc_norm=False, act_layer='gelu_tanh',
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)
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model = _create_vision_transformer(
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'vit_so400m_patch16_siglip_gap_256', pretrained=pretrained, **dict(model_args, **kwargs))
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