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convnextv2_large.fcmae_ft_in22k_in1k_384

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convnextv2_large.fcmae_ft_in22k_in1k_384
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{
  "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"
  }
}