code: def load_from_pretrained(self, url_or_filename, use_distill=True):
      _, msg = super().load_from_pretrained(url_or_filename)
  
      if use_distill and any(["_m" in k for k in msg.missing_keys]):
          # this is required when initializing the model from TA pre-trained weights
          self.copy_params()
  
      return msg
  
imports: from copy import deepcopy
  import torch
  import torch.nn.functional
  from lavis.common.registry import registry
  from lavis.common.utils import get_abs_path
  from lavis.models.albef_models import AlbefBase
  from lavis.models.albef_models.albef_outputs import AlbefIntermediateOutput, AlbefOutput
  from lavis.models.base_model import MomentumDistilationMixin
  from lavis.models.med import BertModel
  from lavis.models.vit import VisionTransformerEncoder
  from torch import nn
  from transformers import BertConfig
label_desc: Use image node_id 6 for calling the AlbefNLVR obj's underlying member method code with example usage: obj.load_from_pretrained(url_or_filename, use_distill) and returns: msg