chunk_content: gth", truncation=True, return_tensors="pt")
      labels = tokenizer(targets, max_length=2, padding="max_length", truncation=True, return_tensors="pt")
      labels = labels["input_ids"]
      labels[labels == tokenizer.pad_token_id] = -100
      model_inputs["labels"] = labels
      return model_inputs
  Use the map function to apply the preprocess_function to the dataset. You can remove the unprocessed columns since the model doesn’t need them anymore:
  
  