Forgot about datcomp b32 models

Author: rwightman

timm/models/vision_transformer.py

@@ -1435,11 +1435,11 @@ def _cfg(url='', **kwargs):
         mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, crop_pct=1.0, num_classes=1280),
 
     'vit_base_patch32_clip_224.datacompxl': _cfg(
-        hf_hub_id='laion/',
+        hf_hub_id='laion/CLIP-ViT-B-32-DataComp.XL-s13B-b90K',
         hf_hub_filename='open_clip_pytorch_model.bin',
         mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, crop_pct=1.0, num_classes=512),
     'vit_base_patch32_clip_256.datacompxl': _cfg(
-        hf_hub_id='laion/',
+        hf_hub_id='laion/CLIP-ViT-B-32-256x256-DataComp-s34B-b86K',
         hf_hub_filename='open_clip_pytorch_model.bin',
         mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD,
         crop_pct=1.0, input_size=(3, 256, 256), num_classes=512),
@@ -1994,6 +1994,17 @@ def vit_base_patch32_clip_224(pretrained=False, **kwargs) -> VisionTransformer:
     return model
 
 
+@register_model
+def vit_base_patch32_clip_256(pretrained=False, **kwargs) -> VisionTransformer:
+    """ ViT-B/32 CLIP image tower @ 256x256
+    """
+    model_args = dict(
+        patch_size=32, embed_dim=768, depth=12, num_heads=12, pre_norm=True, norm_layer=nn.LayerNorm)
+    model = _create_vision_transformer(
+        'vit_base_patch32_clip_256', pretrained=pretrained, **dict(model_args, **kwargs))
+    return model
+
+
 @register_model
 def vit_base_patch32_clip_384(pretrained=False, **kwargs) -> VisionTransformer:
     """ ViT-B/32 CLIP image tower @ 384x384