code: def test_t5_s2s(self):
      text = "sequence test { text }"
      finetune_model = HFS2S(
          base_model=HFT5,
          n_epochs=100,
          batch_size=1,
      )
      finetune_model.fit([text] * 5, [text] * 5)
      finetune_model.save("test.jl")
      self.assertEqual(finetune_model.predict([text]), [text])
      self.assertEqual(
          len(finetune_model.predict([text, "Some other text"])), 2
      )
      loaded_model = HFS2S.load("test.jl")
      self.assertEqual(loaded_model.predict([text]), [text])
  
imports: import os
  import json
  import unittest
  import numpy
  import pytest
  import tensorflow
  import joblib
  from transformers import AutoTokenizer, TFAutoModel, BertTokenizer
  from finetune import SequenceLabeler, DocumentLabeler
  from finetune.base_models import LayoutLM
  from finetune.base_models.huggingface.models import HFBert, HFElectraGen, HFElectraDiscrim, HFXLMRoberta, HFT5, HFAlbert, HFDebertaV3Base
  from finetune.target_models.seq2seq import HFS2S
  from sklearn.model_selection import train_test_split
  from finetune.encoding.sequence_encoder import finetune_to_indico_sequence
label_desc: Use image node_id 6 for calling the TestHuggingFace obj's underlying member method code with example usage: obj.test_t5_s2s() without return types