text: from typing import Sequence
  from packaging.version import parse
  from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
  import argparse
  
  model = AutoModelForTokenClassification.from_pretrained('PlanTL-GOB-ES/roberta-base-ca-cased-te',
                                                          use_auth_token=True)
  tokenizer = AutoTokenizer.from_pretrained('PlanTL-GOB-ES/roberta-base-ca-cased-te',
                                                          use_auth_token=True)
  pipe = pipeline('zero-shot-classification', model=model, tokenizer=tokenizer)
  
  parser = argparse.ArgumentParser()
  parser.add_argument('--text')
  parser.add_argument('--labels', nargs='+')
  args = parser.parse_args()
  
  text = 'Els pressupostos catalans assumeixen un rècord inversor gràcies als fons de la UE.' 
  labels = ["política", "esport", "notícies", "societat"]
  labels = ["notícies", "esport"]
  # result = pipe(sequences=args.text, candidate_labels=args.labels, hypothesis_template="aquest exemple és {}.")
  result = pipe(sequences=text, candidate_labels=labels, hypothesis_template="aquest exemple és {}.")
  print(result)