def register_subcommand(parser: ArgumentParser):
        """
        Register this command to argparse so it's available for the transformer-cli

        Args:
            parser: Root parser to register command-specific arguments
        """
        train_parser = parser.add_parser(
            "pt-to-tf",
            help=(
                "CLI tool to run convert a transformers model from a PyTorch checkpoint to a TensorFlow checkpoint."
                " Can also be used to validate existing weights without opening PRs, with --no-pr."
            ),
        )
        train_parser.add_argument(
            "--model-name",
            type=str,
            required=True,
            help="The model name, including owner/organization, as seen on the hub.",
        )
        train_parser.add_argument(
            "--local-dir",
            type=str,
            default="",
            help="Optional local directory of the model repository. Defaults to /tmp/{model_name}",
        )
        train_parser.add_argument(
            "--max-error",
            type=float,
            default=MAX_ERROR,
            help=(
                f"Maximum error tolerance. Defaults to {MAX_ERROR}. This flag should be avoided, use at your own risk."
            ),
        )
        train_parser.add_argument(
            "--new-weights",
            action="store_true",
            help="Optional flag to create new TensorFlow weights, even if they already exist.",
        )
        train_parser.add_argument(
            "--no-pr", action="store_true", help="Optional flag to NOT open a PR with converted weights."
        )
        train_parser.add_argument(
            "--push",
            action="store_true",
            help="Optional flag to push the weights directly to `main` (requires permissions)",
        )
        train_parser.add_argument(
            "--extra-commit-description",
            type=str,
            default="",
            help="Optional additional commit description to use when opening a PR (e.g. to tag the owner).",
        )
        train_parser.add_argument(
            "--override-model-class",
            type=str,
            default=None,
            help="If you think you know better than the auto-detector, you can specify the model class here. "
            "Can be either an AutoModel class or a specific model class like BertForSequenceClassification.",
        )
        train_parser.set_defaults(func=convert_command_factory)

        Register this command to argparse so it's available for the transformer-cli

        Args:
            parser: Root parser to register command-specific arguments
        
dpkd/transformers/src/transformers/commands/pt_to_tf.py