input: Write a python function to load a pre-trained model, make a prediction on input data, and return the sentiment as 'Positive' or 'Negative'.
  assert predict_sentiment("This movie was amazing!") == 'Positive'
  assert predict_sentiment("I did not like this movie at all.") == 'Negative'
  assert predict_sentiment("The plot was really intriguing and well-executed.") == 'Positive'
output: def predict_sentiment(text):
      from transformers import pipeline
      sentiment_pipeline = pipeline("sentiment-analysis")
      result = sentiment_pipeline(text)[0]
      return 'Positive' if result['label'] == 'POSITIVE' else 'Negative'