src/transformers/models/deberta/modeling_tf_deberta.py/TFDebertaForMaskedLM/__init__
class TFDebertaForMaskedLM:    def __init__(self, config: DebertaConfig, *inputs, **kwargs):
        super().__init__(config, *inputs, **kwargs)

        if config.is_decoder:
            logger.warning(
                "If you want to use `TFDebertaForMaskedLM` make sure `config.is_decoder=False` for "
                "bi-directional self-attention."
            )

        self.deberta = TFDebertaMainLayer(config, name="deberta")
        self.mlm = TFDebertaOnlyMLMHead(config, input_embeddings=self.deberta.embeddings, name="cls")