code: def get_model(self, model_name):
      local_rank = int(os.getenv("LOCAL_RANK", "0"))
      model_config = AutoConfig.from_pretrained(model_name)
      model_config.dropout = 0.0
      model = AutoModelForCausalLM.from_pretrained(
          model_name, config=model_config
      )
      # Make the model smaller so we can run it on a single GPU in CI
      _ = [model.model.layers.pop(-1) for _ in range(8)]
      model = model.half()
      model = model.to(
          f"{get_accelerator().device_name()}:{local_rank}"
      )
      return model
  
file_path: DeepSpeed/tests/unit/hybrid_engine/test_he_llama.py
imports: import os
  import torch
  import pytest
  import deepspeed
  from deepspeed.ops.op_builder import OpBuilder
  from unit.common import DistributedTest
  from deepspeed.accelerator import get_accelerator
  from transformers import AutoConfig, AutoTokenizer, AutoModelForCausalLM
  from deepspeed.ops.op_builder import InferenceBuilder
label_desc: Use image node_id 2 for calling the TestHybridEngineLlama obj's underlying member method code with example usage: obj.get_model(model_name) and returns: model