chunk_content: ify the sentences:
  
  
  	Copied
  with torch.no_grad():
      outputs = model(**inputs).logits
      print(outputs)
  
  paraphrased_text = torch.softmax(outputs, dim=1).tolist()[0]
  for i in range(len(classes)):
      print(f"{classes[i]}: {int(round(paraphrased_text[i] * 100))}%")
  "not equivalent: 4%"
  "equivalent: 96%"
  