code: def __init__(
      self, cfg: DictConfig, trainer: Trainer = None, no_lm_init=True
  ):
      self.cfg = cfg
      super().__init__(cfg=cfg, trainer=trainer, no_lm_init=no_lm_init)
  
file_path: NeMo/nemo/collections/nlp/models/question_answering/qa_base_model.py
imports: from typing import Optional
  import torch
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from nemo.collections.nlp.data.question_answering.data_processor.qa_processing import EVALUATION_MODE, INFERENCE_MODE, TRAINING_MODE
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new BaseQAModel object from inherited base classes: NLPModel with example: obj = BaseQAModel(cfg, trainer, no_lm_init)