code: def bert_model(
      pretrained_model_name_or_path: str = "bert-base-uncased",
      num_labels: int = 4,
  ):
      return BertForSequenceClassification.from_pretrained(
          pretrained_model_name_or_path=pretrained_model_name_or_path,
          num_labels=num_labels,
      )
  
file_path: transfer-nlp/experiments/bert/bert.py
imports: import logging
  from pathlib import Path
  from typing import Tuple
  import numpy
  import pandas
  from pytorch_pretrained_bert import BertTokenizer, BertForSequenceClassification, BertAdam
  from tqdm import tqdm
  from transfer_nlp.loaders.loaders import DatasetSplits, DataFrameDataset
  from transfer_nlp.loaders.vectorizers import Vectorizer
  from transfer_nlp.loaders.vocabulary import Vocabulary
  from transfer_nlp.plugins.config import register_plugin, ExperimentConfig
label_desc: Use image node_id 1 for calling a global function with example usage: bert_model(pretrained_model_name_or_path, num_labels) and returns: BertForSequenceClassification