(pretrained=False, in_22k=False, **kwargs)
| 184 | |
| 185 | @register_model |
| 186 | def convnext_large(pretrained=False, in_22k=False, **kwargs): |
| 187 | model = ConvNeXt(depths=[3, 3, 27, 3], dims=[192, 384, 768, 1536], **kwargs) |
| 188 | if pretrained: |
| 189 | url = model_urls['convnext_large_22k'] if in_22k else model_urls['convnext_large_1k'] |
| 190 | checkpoint = torch.hub.load_state_dict_from_url(url=url, map_location="cpu") |
| 191 | model.load_state_dict(checkpoint["model"]) |
| 192 | return model |
| 193 | |
| 194 | @register_model |
| 195 | def convnext_xlarge(pretrained=False, in_22k=False, **kwargs): |