optimum/executorch/modeling.py [509:531]:
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    def text_generation(
        self,
        tokenizer: "PreTrainedTokenizer",
        prompt: str,
        echo: bool = True,
        max_seq_len: Optional[int] = None,
    ):
        """
        Perform text generation task for a given prompt using the ExecuTorch model.

        Args:
            tokenizer (`PreTrainedTokenizer`):
                The tokenizer used to encode and decode the prompt and output.
            prompt (`str`):
                The text prompt to complete.
            echo (`bool`, *optional*):
                Whether to include prompt tokens in the generated output. Defaults to `True`.
            max_seq_len (`int`, *optional*):
                Maximum sequence length for the generated output.
                Defaults to None and uses the model's `max_cache_size` attribute.
                Will be truncated to maximal cache size if larger than `max_cache_size`.
        """
        self.tokenizer = tokenizer
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optimum/executorch/modeling.py [729:751]:
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    def text_generation(
        self,
        tokenizer: "PreTrainedTokenizer",
        prompt: str,
        echo: bool = True,
        max_seq_len: Optional[int] = None,
    ):
        """
        Perform text generation task for a given prompt using the ExecuTorch model.

        Args:
            tokenizer (`PreTrainedTokenizer`):
                The tokenizer used to encode and decode the prompt and output.
            prompt (`str`):
                The text prompt to complete.
            echo (`bool`, *optional*):
                Whether to include prompt tokens in the generated output. Defaults to `True`.
            max_seq_len (`int`, *optional*):
                Maximum sequence length for the generated output.
                Defaults to None and uses the model's `max_cache_size` attribute.
                Will be truncated to maximal cache size if larger than `max_cache_size`.
        """
        self.tokenizer = tokenizer
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