y of keyword arguments, *optional*):
                Can be used to update the configuration object (after it being loaded) and initiate the model (e.g.,
                `output_attentions=True`).

                - To update the question_encoder configuration, use the prefix *question_encoder_* for each
                  configuration parameter.
                - To update the generator configuration, use the prefix *generator_* for each configuration parameter.
                - To update the parent model configuration, do not use a prefix for each configuration parameter.

                Behaves differently depending on whether a `config` is provided or automatically loaded.

        Example:

        ```python
        >>> from transformers import RagRetriever, TFRagModel

        >>> # initialize a RAG from two pretrained models.
        >>> model = TFRagModel.from_pretrained_question_encoder_generator(
        ...     "facebook/dpr-question_encoder-single-nq-base", "t5-small"
        ... )
        >>> # alternatively, initialize from pytorch pretrained models can also be done
        >>> model = TFRagModel.from_pretrained_question_encoder_generator(
        ...     "facebook/dpr-question_encoder-single-nq-base",
        ...     "facebook/bart-base",
        ...     generator_from_pt=True,
        ...     question_encoder_from_pt=True,
        ... )

        >>> # saving model after fine-tuning
        >>> model.save_pretrained("./rag")

        >>> # load retriever
        >>> retriever = RagRetriever.from_pretrained(
        ...     "facebook/rag-token-base", index_name="exact", use_dummy_dataset=True
        ... )
        >>> # load fine-tuned model with retriever
        >>> model = TFRagModel.from_pretrained("./rag", retriever=retriever)
        ```c