code: def instantiate_model(self):
      if hasattr(self._datamodule, "num_labels"):
          self.model_cfg.config.num_labels = self._datamodule.num_labels
      logger.info(f"Instantiating model <{self.model_cfg._target_}>")
      # Huggingface models need the config object to in instantiated first
      # We have to convert the config to dict so that we can assign model_cfg.config = BertConfig.
      # The reason for that is that we can't call hydra.util.instantiate(self.model_cfg, config=config)
      # since "config" is a kwarg name that's already in hydra.util.instantiate
      model_cfg = OmegaConf.to_container(self.model_cfg, resolve=True)
      model_cfg["config"] = hydra.utils.instantiate(
          model_cfg.pop("config"), _recursive_=False
      )
      model_cfg["config"].mlp_cfg = getattr(
          self.model_cfg.config, "mlp_cfg", None
      )
      self.model = hydra.utils.instantiate(model_cfg, _recursive_=False)
  
imports: from typing import Any, List
  import inspect
  import torch
  import hydra
  from pytorch_lightning import LightningModule, LightningDataModule
  from torchmetrics import MetricCollection
  from einops import rearrange
  from omegaconf import OmegaConf
  from src.utils.utils import get_logger
  from src.optim.param_grouping import group_parameters_for_optimizer
  from src.utils.checkpoint import load_checkpoint
  import datasets
label_desc: Use image node_id 1 for calling the GLUETransformer obj's underlying member method code with example usage: obj.instantiate_model() without return types