code: def basic_translation_scenario():
      """Create a basic transformers translation model and tokenizer."""
      AutoTokenizer = pytest.importorskip("transformers").AutoTokenizer
      AutoModelForSeq2SeqLM = pytest.importorskip(
          "transformers"
      ).AutoModelForSeq2SeqLM
  
      # Use a *tiny* tokenizer model, to keep tests running as fast as possible.
      # Nb. At time of writing, this pretrained model requires "protobuf==3.20.3".
      # name = "mesolitica/finetune-translation-t5-super-super-tiny-standard-bahasa-cased"
      # name = "Helsinki-NLP/opus-mt-en-es"
      name = "hf-internal-testing/tiny-random-BartModel"
      tokenizer = AutoTokenizer.from_pretrained(name)
      model = AutoModelForSeq2SeqLM.from_pretrained(name)
  
      # define the input sentences we want to translate
      data = [
          "In this picture, there are four persons: my father, my mother, my brother and my sister.",
          "Transformers have rapidly become the model of choice for NLP problems, replacing older recurrent neural network models",
      ]
  
      return model, tokenizer, data
  
label_desc: Use image node_id 1 for calling a global function with example usage: basic_translation_scenario() and returns: model,  tokenizer,  data