code: def _setup_models_for_neftune():
      module_without_hook = AutoModelForCausalLM.from_pretrained(
          TEST_MODEL_NAME
      )
      module_with_hook = AutoModelForCausalLM.from_pretrained(
          TEST_MODEL_NAME
      )
  
      # Only module_with_hook should have the NEFTuneHook
      neftune_hook = NEFTuneHook(neftune_noise_alpha=5)
      module_with_hook = neftune_hook.activate_hook(module_with_hook)
  
      return module_without_hook, module_with_hook
  
imports: import pytest
  import torch
  from transformers import AutoConfig, AutoModelForCausalLM
  from ludwig.constants import LOGITS, PREDICTIONS, PROBABILITIES
  from ludwig.modules.training_hooks import NEFTuneHook
  from ludwig.utils.llm_utils import add_left_padding, create_attention_mask, FALLBACK_CONTEXT_LEN, find_last_matching_index, generate_merged_ids, get_context_len, get_realigned_target_and_prediction_tensors_for_inference, has_padding_token, pad_target_tensor_for_fine_tuning, remove_left_padding
  from ludwig.utils.tokenizers import HFTokenizer
label_desc: Use image node_id 17 for calling a global function with example usage: _setup_models_for_neftune() and returns: module_without_hook,  module_with_hook