code: def _build_model(self):
      self.model = Word2tag.load_checkpoint(
          self.checkpoint_save_path, "best.pt"
      ).to(self.device)
  
      self.inference_tool = ClassifierInferenceWrapper(
          cfg=self.opt,
          model=self.model,
          label_names=self.tag_types,
          dataset=ConllDataset_inference,
          data_item=SequenceLabelingDataItem,
          topology_builder=LineBasedGraphConstruction,
          lower_case=True,
          tokenizer=None,
      )
  
imports: import argparse
  import os
  import torch
  import torch.backends.cudnn
  import torch.multiprocessing
  from graph4nlp.pytorch.data.dataset import SequenceLabelingDataItem
  from graph4nlp.pytorch.inference_wrapper.classifier_inference_wrapper import ClassifierInferenceWrapper
  from graph4nlp.pytorch.modules.config import get_basic_args
  from graph4nlp.pytorch.modules.utils.config_utils import get_yaml_config, update_values
  from graph4nlp.pytorch.modules.utils.generic_utils import to_cuda
  from conll import ConllDataset_inference
  from conlleval import evaluate
  from line_graph_construction import LineBasedGraphConstruction
  from model import Word2tag
label_desc: Use image node_id 2 for calling the Conll obj's underlying member method code with example usage: obj._build_model() without return types