code: def _optimize_pre(model):
      from transformers.modeling_utils import PreTrainedModel
  
      # All huggingface format models are inherited from `PreTrainedModel`
      if not isinstance(model, PreTrainedModel):
          logger.info(
              "Only HuggingFace Transformers models are currently "
              "supported for further optimizations"
          )
          return model
      # for rwkv models (verified RWKV/rwkv-4-world-7b)
      if model.config.model_type == "rwkv":
          model.rwkv._rescale_layers()
      # process NormHead module in Baichuan2 7B and 13B
      if (
          model.config.model_type == "baichuan"
          and model.config.vocab_size == 125696
      ):
          # NormHead do normalization on the weights just once at inference time.
          # so we do it in advance and convert it to Linear so that it can be replaced.
          # modeling_module_name = model.__class__.__module__
          # module = importlib.import_module(modeling_module_name)
          if hasattr(model, "lm_head") and model.lm_head is not None:
              # do we need to check the class instance?
              vocab_size, hidden_size = model.lm_head.weight.shape
              lm_head_weight_data = model.lm_head.weight.data
              model.lm_head = nn.Linear(
                  hidden_size,
                  vocab_size,
                  bias=False,
                  device=lm_head_weight_data.device,
              )
              # In which case we are NOT loading the normalized weights
              if model.lm_head.weight.data.device != "meta":
                  norm_weight = nn.functional.normalize(
                      lm_head_weight_data
                  )
                  model.lm_head.weight.data = norm_weight
      return model
  
imports: import platform
  import torch
  import torch.nn
  from accelerate import init_empty_weights
  import warnings
  import transformers
  import importlib.util
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  from .utils import logger
  from typing import Union
  import numpy
  import os
  from bigdl.llm.utils.common import invalidInputError
label_desc: Use image node_id 8 for calling a global function with example usage: _optimize_pre(model) and returns: model, model