y_shared_bottleneck (`bool`, *optional*, defaults to `True`):
            Whether to use the same linear transformation for query&key in the bottleneck.
        num_feedforward_networks (`int`, *optional*, defaults to 4):
            Number of FFNs in a block.
        normalization_type (`str`, *optional*, defaults to `"no_norm"`):
            The normalization type in MobileBERT.
        classifier_dropout (`float`, *optional*):
            The dropout ratio for the classification head.

    Examples:

    ```python
    >>> from transformers import MobileBertConfig, MobileBertModel

    >>> # Initializing a MobileBERT configuration
    >>> configuration = MobileBertConfig()

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

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

    Attributes: pretrained_config_archive_map (Dict[str, str]): A dictionary containing all the available pre-trained
    checkpoints.
    Z
mobileberté:w