code: def get_learner(self):
      from .data_ner import BertNERDataBunch
      from .learner_ner import BertNERLearner
  
      databunch = BertNERDataBunch(
          self.label_path,
          self.tokenizer,
          train_file=None,
          val_file=None,
          batch_size_per_gpu=32,
          max_seq_length=512,
          multi_gpu=False,
          model_type=self.model_type,
          no_cache=True,
      )
  
      learner = BertNERLearner.from_pretrained_model(
          databunch,
          self.model_path,
          device=self.device,
          logger=None,
          output_dir=None,
          warmup_steps=0,
          multi_gpu=False,
          is_fp16=False,
          logging_steps=0,
      )
  
      return learner
  
imports: import torch
  from pathlib import Path
  from .onnx_helper import load_model
  from .learner_ner import group_entities
  from .data_ner import get_labels
  from transformers import AutoTokenizer
  import numpy
  import warnings
label_desc: Use image node_id 2 for calling the BertNERPredictor obj's underlying member method code with example usage: obj.get_learner() and returns: learner