src/transformers/models/rembert/modeling_tf_rembert.py/TFRemBertForMaskedLM/__init__
class TFRemBertForMaskedLM:    def __init__(self, config: RemBertConfig, *inputs, **kwargs):
        super().__init__(config, *inputs, **kwargs)

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

        self.rembert = TFRemBertMainLayer(config, name="rembert", add_pooling_layer=False)
        self.mlm = TFRemBertMLMHead(config, input_embeddings=self.rembert.embeddings, name="mlm___cls")