code: def __init__(self, config):
      super().__init__(config)
      self.model = Model(config)
  
      self.lm_head = nn.Linear(
          config.hidden_size, config.vocab_size, bias=False
      )
  
      # Initialize weights and apply final processing
      self.post_init()
  
imports: from .configuration_baichuan import BaiChuanConfig
  from transformers import PreTrainedModel, add_start_docstrings
  from transformers.activations import ACT2FN
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, SequenceClassifierOutputWithPast
  from transformers.utils import logging, add_start_docstrings_to_model_forward, replace_return_docstrings
  import math
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
label_desc: Use image node_id 1 to create a new BaiChuanForCausalLM object from inherited base classes: PreTrainedModel with example: obj = BaiChuanForCausalLM(config)