class_docstr: Base class for NLP Models.
      
class_docstr_tok: ["Base","class","for","NLP","Models","."]
code: def _unpack_nemo_file(path2file: str, out_folder: str) -> str:
      return super(NLPModel, NLPModel)._unpack_nemo_file(
          path2file, out_folder
      )
  
imports: import copy
  import hashlib
  import json
  import os
  from typing import Any, Mapping, Optional, Union
  import torch
  from lightning_fabric.utilities.cloud_io import _load
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from pytorch_lightning.core.saving import _load_state
  from pytorch_lightning.core.saving import load_hparams_from_tags_csv, load_hparams_from_yaml
  from pytorch_lightning.utilities import rank_zero_only
  from pytorch_lightning.utilities.migration import pl_legacy_patch
  from transformers import TRANSFORMERS_CACHE
  from nemo.collections.common.tokenizers.huggingface.auto_tokenizer import AutoTokenizer
  from nemo.collections.nlp.modules import BertModule
  from nemo.collections.nlp.modules.common.huggingface.huggingface_utils import VOCAB_FILE_NAME
  from nemo.collections.nlp.modules.common.lm_utils import get_lm_model
  from nemo.collections.nlp.modules.common.megatron.megatron_utils import MEGATRON_CONFIG_MAP, get_megatron_pretrained_bert_models
  from nemo.collections.nlp.modules.common.tokenizer_utils import get_tokenizer
  from nemo.collections.nlp.parts.nlp_overrides import NLPSaveRestoreConnector
  from nemo.core.classes import ModelPT
  from nemo.core.classes.exportable import Exportable
  from nemo.core.connectors.save_restore_connector import SaveRestoreConnector
  from nemo.utils import AppState, logging
label_desc: Use image node_id 6 for calling the NLPModel obj's underlying member method code with example usage: obj._unpack_nemo_file(path2file, out_folder) and returns: super