code: def gutenberg_spacy_ner(mocked_client):
      from datasets import load_dataset
  
      dataset = "gutenberg_spacy_ner"
      dataset_ds = load_dataset(
          "argilla/gutenberg_spacy-ner",
          split="train",
          # This revision does not includes the vectors info, so tests will pass
          revision="fff5f572e4cc3127f196f46ba3f9914c6fd0d763",
      )
  
      dataset_rb = argilla.read_datasets(
          dataset_ds, task="TokenClassification"
      )
  
      delete_ignoring_errors(dataset)
  
      argilla.log(name=dataset, records=dataset_rb)
  
      return dataset
  
file_path: argilla/tests/integration/metrics/test_common_metrics.py
imports: import argilla
  import argilla
  import argilla.client.singleton
  import pytest
  from argilla.client.api import log
  from argilla.client.models import TextClassificationRecord
  from argilla.metrics.commons import keywords, records_status, text_length
  from tests.integration.utils import delete_ignoring_errors
label_desc: Use image node_id 1 for calling a global function with example usage: gutenberg_spacy_ner(mocked_client) and returns: dataset