code: def create_text_classification_pipeline():
      # load the model and tokenizer
      tokenizer = AutoTokenizer.from_pretrained(
          "nateraw/bert-base-uncased-emotion", use_fast=True
      )
      model = AutoModelForSequenceClassification.from_pretrained(
          "nateraw/bert-base-uncased-emotion"
      )
  
      # build a pipeline object to do predictions
      pred = pipeline(
          "text-classification",
          model=model,
          tokenizer=tokenizer,
          device=-1,
          return_all_scores=True,
      )
      return pred
  
imports: import os
  import zipfile
  import datasets
  import pandas
  from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
  from raiutils.common.retries import retry_function
  from responsibleai_text.common.constants import QuestionAnsweringFields
label_desc: Use image node_id 6 for calling a global function with example usage: create_text_classification_pipeline() and returns: pred