from the generated text. A lower learning rate will result in
    slower adjustments, while a higher learning rate will make
    the algorithm more responsive. (Default: 0.1)"""
    mirostat_tau: Optional[float]
    """Controls the balance between coherence and diversity
    of the output. A lower value will result in more focused and
    coherent text. (Default: 5.0)"""
    num_ctx: Optional[int]
    """Sets the size of the context window used to generate the
    next token. (Default: 2048)	"""
    num_gpu: Optional[int]
    """The number of GPUs to use. On macOS it defaults to 1 to
    enable metal support, 0 to disable."""
    num_thread: Optional[int]
    """Sets the number of threads to use during computation.
    By default, Ollama will detect this for optimal performance.
    It is recommended to set this value to the number of physical
    CPU cores your system has (as opposed to the logical number of cores)."""
    repeat_last_n: Optional[int]
    """Sets how far back for the model to look back to prevent
    repetition. (Default: 64, 0 = disabled, -1 = num_ctx)"""
    repeat_penalty: Optional[float]
    """Sets how strongly to penalize repetitions. A higher value (e.g., 1.5)
    will penalize repetitions more strongly, while a lower value (e.g., 0.9)
    will be more lenient. (Default: 1.1)"""
    temperature: Optional[float]
    """The temperature of the model. Increasing the temperature will
    make the model answer more creatively. (Default: 0.8)"""
    stop: Optional[List[str]]