code: def vit_base_patch16_224(pretrained=True, **kwargs):
      """ViT-Base (ViT-B/16) from original paper
      (https://arxiv.org/abs/2010.11929).
      ImageNet-1k weights fine-tuned from in21k @ 224x224,
      source https://github.com/google-research/vision_transformer.
      """
      from avalanche.models.timm_vit import _create_vision_transformer
  
      model_kwargs = dict(
          patch_size=16, embed_dim=768, depth=12, num_heads=12, **kwargs
      )
      model = _create_vision_transformer(
          "vit_base_patch16_224", pretrained=pretrained, **model_kwargs
      )
      return model
  
file_path: avalanche/avalanche/models/vit.py
imports: from avalanche.models import SimpleMLP
label_desc: Use image node_id 2 for calling a global function with example usage: vit_base_patch16_224(pretrained) and returns: model