code: def load_embeddings() -> t.Tuple[np.array, np.array]:
      """Load and return the embeddings of the SCIERC dataset calculated by OpenAI.
  
      Returns
      -------
      embeddings : np.Tuple[np.array, np.array]
          Embeddings for the SCIERC dataset.
      """
      train_embeddings = read_and_save_data(
          ASSETS_DIR,
          "train_embeddings.npy",
          _TRAIN_EMBEDDINGS_URL,
          file_type="npy",
          to_numpy=True,
      )
      test_embeddings = read_and_save_data(
          ASSETS_DIR,
          "test_embeddings.npy",
          _TEST_EMBEDDINGS_URL,
          file_type="npy",
          to_numpy=True,
      )
      return train_embeddings, test_embeddings
  
file_path: deepchecks/deepchecks/nlp/datasets/token_classification/scierc_ner.py
imports: import pathlib
  import typing
  import warnings
  import numpy
  import pandas
  from deepchecks.nlp import TextData
  from deepchecks.utils.builtin_datasets_utils import read_and_save_data
label_desc: Use image node_id 3 for calling a global function with example usage: load_embeddings() and returns: train_embeddings,  test_embeddings