chunk_content: inputs["input_ids"][i][:max_length])
          model_inputs["attention_mask"][i] = torch.tensor(model_inputs["attention_mask"][i][:max_length])
          labels["input_ids"][i] = torch.tensor(labels["input_ids"][i][:max_length])
      model_inputs["labels"] = labels["input_ids"]
      return model_inputs
  Use the map function to apply the preprocess_function to the entire dataset. You can remove the unprocessed columns since the model won’t need them:
  
  