code: def load_data(limit=0, split=0.8):
      
      # Partition off part of the train data for evaluation
      train_data, _ = thinc.extra.datasets.imdb()
      random.shuffle(train_data)
      train_data = train_data[-limit:]
      texts, labels = zip(*train_data)
      cats = [{"POSITIVE": bool(y), "NEGATIVE": not bool(y)} for y in labels]
      split = int(len(train_data) * split)
      return (texts[:split], cats[:split]), (texts[split:], cats[split:])
docs: Load data from the IMDB dataset.