code: def vit_large_patch16_224(num_classes: int = 1000):
      """
      ViT-Large model (ViT-L/16) from original paper (https://arxiv.org/abs/2010.11929).
      ImageNet-1k weights @ 224x224, source https://github.com/google-research/vision_transformer.
      weights ported from official Google JAX impl:
      链接: https://pan.baidu.com/s/1cxBgZJJ6qUWPSBNcE4TdRQ  密码: qqt8
      """
      model = VisionTransformer(
          img_size=224,
          patch_size=16,
          embed_dim=1024,
          depth=24,
          num_heads=16,
          representation_size=None,
          num_classes=num_classes,
      )
      return model
  
imports: from functools import partial
  from collections import OrderedDict
  import torch
  import torch.nn
label_desc: Use image node_id 7 for calling a global function with example usage: vit_large_patch16_224(num_classes) and returns: model