oint name and this method will try to instantiate it using `model_classes`. Since we don't want to
    instantiate the model twice, this model is returned for use by the pipeline.

    If both frameworks are installed and available for `model`, PyTorch is selected.

    Args:
        model (`str`, [`PreTrainedModel`] or [`TFPreTrainedModel`]):
            The model to infer the framework from. If `str`, a checkpoint name. The model to infer the framewrok from.
        model_classes (dictionary `str` to `type`, *optional*):
            A mapping framework to class.
        task (`str`):
            The task defining which pipeline will be returned.
        model_kwargs:
            Additional dictionary of keyword arguments passed along to the model's `from_pretrained(...,
            **model_kwargs)` function.

    Returns:
        `Tuple`: A tuple framework, model.
    rd