code: def swap_model(
      model: HFBertModel, data_type, lib_path, remove_padding=False
  ) -> FasterBertModel:
      # bert model need some custom code to call the custom encoder
      # so we need to use custom bert class
      new_model = FasterBertModel(model.config)
      new_model.load_state_dict(model.state_dict())
      swap_bert_encoder(new_model, data_type, lib_path, remove_padding)
      return new_model
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/faster_transformer/bert/__init__.py
imports: import os
  from nebullvm.operations.optimizations.compilers.faster_transformer.bert.modeling_bert import BertModel
  from nebullvm.operations.optimizations.compilers.faster_transformer.bert.modeling_bert import CustomEncoder, EncoderWeights
  from nebullvm.operations.optimizations.compilers.utils import get_faster_transformer_repo_path
  from nebullvm.optional_modules.huggingface import BertModel
  from nebullvm.optional_modules.torch import torch
label_desc: Use image node_id 2 for calling a global function with example usage: swap_model(model, data_type, lib_path, remove_padding) and returns: new_model