document.write('
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  1. from transformers import pipeline
  2.  
  3. model_names = ["model1", "model2", "model3"]
  4. pipelines = [pipeline("sentiment-analysis", model=model_name) for model_name in model_names]
  5.  
  6. def ensemble_predict(text):
  7. predictions = [pipeline(text)[0] for pipeline in pipelines]
  8. labels = [pred["label"] for pred in predictions]
  9. scores = [pred["score"] for pred in predictions]
  10.  
  11. # Majority voting
  12. final_label = max(set(labels), key=labels.count)
  13. final_score = sum(scores) / len(scores)
  14.  
  15. return {"label": final_label, "score": final_score}
  16.  
  17. text = "The company reported strong quarterly earnings, exceeding market expectations."
  18. result = ensemble_predict(text)
  19. print(result)
  20.  
');