| { | |
| "architecture": "convnextv2_large", | |
| "num_classes": 1000, | |
| "num_features": 1536, | |
| "pretrained_cfg": { | |
| "tag": "fcmae_ft_in22k_in1k_384", | |
| "custom_load": false, | |
| "input_size": [ | |
| 3, | |
| 384, | |
| 384 | |
| ], | |
| "fixed_input_size": false, | |
| "interpolation": "bicubic", | |
| "crop_pct": 1.0, | |
| "crop_mode": "squash", | |
| "mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "num_classes": 1000, | |
| "pool_size": [ | |
| 12, | |
| 12 | |
| ], | |
| "first_conv": "stem.0", | |
| "classifier": "head.fc", | |
| "license": "cc-by-nc-4.0", | |
| "origin_url": "https://github.com/facebookresearch/ConvNeXt-V2", | |
| "paper_name": "ConvNeXt-V2: Co-designing and Scaling ConvNets with Masked Autoencoders", | |
| "paper_ids": "arXiv:2301.00808" | |
| } | |
| } |