/2009.13658).
        is_decoder (`bool`, *optional*, defaults to `False`):
            Whether the model is used as a decoder or not. If `False`, the model is used as an encoder.
        use_cache (`bool`, *optional*, defaults to `True`):
            Whether or not the model should return the last key/values attentions (not used by all models). Only
            relevant if `config.is_decoder=True`.
        classifier_dropout (`float`, *optional*):
            The dropout ratio for the classification head.

    Examples:

    ```python
    >>> from transformers import RobertaPreLayerNormConfig, RobertaPreLayerNormModel

    >>> # Initializing a RoBERTa-PreLayerNorm configuration
    >>> configuration = RobertaPreLayerNormConfig()

    >>> # Initializing a model (with random weights) from the configuration
    >>> model = RobertaPreLayerNormModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```z