code: def remove_unused_columns(
      model: nn.Module, dataset: hf_datasets.Dataset
  ) -> None:
      # This method is implemented in transformer's Trainer.
      # Inspect model forward signature to keep only the arguments it accepts.
      signature = inspect.signature(model.forward)
      signature_columns = list(signature.parameters.keys())
      # Labels may be named label or label_ids, the default data collator handles that.
      signature_columns += ["label", "label_ids"]
      columns = [
          k for k in signature_columns if k in dataset.column_names
      ]
      dataset.set_format(type=dataset.format["type"], columns=columns)
  
label_desc: Use image node_id 1 for calling a global function with example usage: remove_unused_columns(model, dataset) without return types