code: def _init_model(self):
      # Load meta model (no memory used)
      with init_empty_weights():
          self.model = AutoModelForCausalLM.from_config(self.config)
          self.model = optimize_model(self.model)
          self.model.tie_weights()
  
      self.layers = (
          [self.model.model.embed_tokens]
          + list(self.model.model.layers)
          + [self.model.model.norm, self.model.lm_head]
      )
  
      # Move buffers to device (not that much GPU memory used)
      for buffer_name, buffer in self.model.named_buffers():
          set_module_tensor_to_device_with_cache(
              self.model,
              buffer_name,
              self.device,
              value=buffer,
              dtype=buffer.dtype,
              cache_dict=self.layer_weight_cache,
              max_cache_num=self.max_cache_num,
          )
  
imports: import argparse
  import gc
  import os
  import time
  import warnings
  from typing import Dict, List, Optional, Union
  import torch
  import torch.nn
  from accelerate import init_empty_weights
  from safetensors.torch import load_file, save_file
  from tqdm.auto import tqdm
  from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer
  from transformers.generation import GenerationMixin
  from transformers.modeling_outputs import CausalLMOutputWithPast
  from bigdl.llm import optimize_model
  from bigdl.llm.transformers.low_bit_linear import FP4Params, LowBitLinear
label_desc: Use image node_id 6 for calling the LowMemoryLlama obj's underlying member method code with example usage: obj._init_model() without return types