code: def _get_pred_probs_labels_from_labelerrors_datasets(dataset_name):
      """Helper function to load data from the labelerrors.com datasets."""
  
      labels_url, pred_probs_url = urls[dataset_name]
      response = requests.get(pred_probs_url)
      response.raise_for_status()
      pred_probs = np.load(
          io.BytesIO(response.content), allow_pickle=True
      )
      response = requests.get(labels_url)
      response.raise_for_status()
      labels = np.load(io.BytesIO(response.content), allow_pickle=True)
      return pred_probs, labels
  
file_path: cleanlab/tests/test_dataset.py
imports: import requests
  import pytest
  import hypothesis.extra.numpy
  import hypothesis.strategies
  import io
  import numpy
  from hypothesis import given, settings
  from cleanlab.dataset import health_summary, find_overlapping_classes, rank_classes_by_label_quality, overall_label_health_score
  from cleanlab.count import estimate_joint, num_label_issues, compute_confident_joint
label_desc: Use image node_id 1 for calling a global function with example usage: _get_pred_probs_labels_from_labelerrors_datasets(dataset_name) and returns: pred_probs,  labels