code: def test_prepare_for_training(self):
      ner_dataset = datasets.load_dataset(
          "argilla/gutenberg_spacy-ner",
          use_auth_token=_HF_HUB_ACCESS_TOKEN,
          split="train",
      )
      rb_dataset: DatasetForTokenClassification = read_datasets(
          ner_dataset, task="TokenClassification"
      )
      for r in rb_dataset:
          r.annotation = [
              (label, start, end)
              for label, start, end, _ in r.prediction
          ]
  
      train = rb_dataset.prepare_for_training()
      assert (set(train.column_names)) == set(
          ["id", "tokens", "ner_tags"]
      )
  
      assert isinstance(train, datasets.Dataset) or isinstance(
          train, datasets.Dataset
      )
      assert "ner_tags" in train.column_names
      assert len(train) == 100
  
      assert train.features["ner_tags"].feature == datasets.ClassLabel(
          names=[
              "O",
              "B-CARDINAL",
              "I-CARDINAL",
              "B-DATE",
              "I-DATE",
              "B-FAC",
              "I-FAC",
              "B-GPE",
              "I-GPE",
              "B-LANGUAGE",
              "I-LANGUAGE",
              "B-LOC",
              "I-LOC",
              "B-NORP",
              "I-NORP",
              "B-ORDINAL",
              "I-ORDINAL",
              "B-ORG",
              "I-ORG",
              "B-PERSON",
              "I-PERSON",
              "B-PRODUCT",
              "I-PRODUCT",
              "B-QUANTITY",
              "I-QUANTITY",
              "B-TIME",
              "I-TIME",
              "B-WORK_OF_ART",
              "I-WORK_OF_ART",
          ]
      )
  
      _push_to_hub_with_retries(
          train,
          repo_id="argilla/_test_token_classification_training",
          token=_HF_HUB_ACCESS_TOKEN,
          private=True,
      )
  
imports: import copy
  import os
  import sys
  from time import sleep
  import datasets
  import pandas
  import pytest
  import spacy
  from argilla.client.datasets import DatasetBase, DatasetForText2Text, DatasetForTextClassification, DatasetForTokenClassification, WrongRecordTypeError, read_datasets, read_pandas
  from argilla.client.models import Text2TextRecord, TextClassificationRecord, TokenClassificationRecord
  from argilla.datasets import TextClassificationSettings
label_desc: Use image node_id 11 for calling the TestDatasetForTokenClassification obj's underlying member method code with example usage: obj.test_prepare_for_training() without return types