code: def glue_classification(
      num_classes, Dataset, name_from_datapath_func
  ):
      def train_valid_datasets_provider():
          """Build train and validation dataset."""
          args = get_args()
          tokenizer = get_tokenizer()
  
          train_dataset = Dataset(
              "training", args.train_data, tokenizer, args.seq_length
          )
          valid_dataset = Dataset(
              "validation", args.valid_data, tokenizer, args.seq_length
          )
  
          return train_dataset, valid_dataset
  
      def model_provider(pre_process=True, post_process=True):
          """Build the model."""
          args = get_args()
          config = core_transformer_config_from_args()
  
          print_rank_0(
              "building classification model for {} ...".format(
                  args.task
              )
          )
          model = Classification(
              config=config,
              num_classes=num_classes,
              num_tokentypes=2,
              pre_process=pre_process,
              post_process=post_process,
          )
  
          return model
  
      def metrics_func_provider():
          """Privde metrics callback function."""
  
          def single_dataset_provider(datapath):
              args = get_args()
              tokenizer = get_tokenizer()
  
              name = name_from_datapath_func(datapath)
              return Dataset(
                  name, [datapath], tokenizer, args.seq_length
              )
  
          return accuracy_func_provider(single_dataset_provider)
  
      """Finetune/evaluate."""
      finetune(
          train_valid_datasets_provider,
          model_provider,
          end_of_epoch_callback_provider=metrics_func_provider,
      )
  
file_path: megatron-lm/tasks/glue/finetune.py
imports: from megatron import get_args
  from megatron import print_rank_0
  from megatron import get_tokenizer
  from megatron.model.classification import Classification
  from tasks.eval_utils import accuracy_func_provider
  from tasks.finetune_utils import finetune
  from megatron.arguments import core_transformer_config_from_args
label_desc: Use image node_id 1 for calling a global function with example usage: glue_classification(num_classes, Dataset, name_from_datapath_func) and returns: train_dataset,  valid_dataset, model, accuracy_func_provider, Dataset