def correct_tables(self, generation: str) -> str:
        """
        Takes a generated string and fixes tables/tabulars to make them match the markdown format needed.

        Args:
            generation (str): The generated text to be postprocessed.

        Returns:
            str: The postprocessed text.

        Example:

        ```python
        correct_tables("\\begin{table} \\begin{tabular}{l l} & \\ \\end{tabular} \\end{table}")
        "\\begin{table}\n\\begin{tabular}{l l} & \\ \\end{tabular}\n\\end{table}"
        ```
        """
        # remove obvious wrong tables
        for l in generation.split("\n"):
            if l.count("\\begin{tabular}") > 15 or l.count("\\multicolumn") > 60 or l.count("&") > 400:
                generation = generation.replace(l, "")
        # whitespace corrections

        generation = generation.replace("\\begin{table} \\begin{tabular}", "\\begin{table}\n\\begin{tabular}")
        generation = generation.replace("\\end{tabular} \\end{table}", "\\end{tabular}\n\\end{table}")
        generation = generation.replace("\\end{table} Tab", "\\end{table}\nTab")

        generation = re.sub(r"(^.+)\\begin{tab", r"\1\n\\begin{tab", generation, flags=re.M)

        # Remove left-aligned empty LaTeX tabular blocks.
        generation = generation.replace(r"\begin{tabular}{l l}  & \\ \end{tabular}", "")
        # Remove tabulars with just 2 newline characters.
        generation = generation.replace("\\begin{tabular}{}\n\n\\end{tabular}", "")
        return generation

        Takes a generated string and fixes tables/tabulars to make them match the markdown format needed.

        Args:
            generation (str): The generated text to be postprocessed.

        Returns:
            str: The postprocessed text.

        Example:

        ```python
        correct_tables("\begin{table} \begin{tabular}{l l} & \ \end{tabular} \end{table}")
        "\begin{table}
\begin{tabular}{l l} & \ \end{tabular}
\end{table}"
        ```
        
dpkd/transformers/src/transformers/models/nougat/tokenization_nougat_fast.py