src/transformers/models/roberta/modeling_tf_roberta.py/TFRobertaForCausalLM/__init__
class TFRobertaForCausalLM:    def __init__(self, config: RobertaConfig, *inputs, **kwargs):
        super().__init__(config, *inputs, **kwargs)

        if not config.is_decoder:
            logger.warning("If you want to use `TFRobertaLMHeadModel` as a standalone, add `is_decoder=True.`")

        self.roberta = TFRobertaMainLayer(config, add_pooling_layer=False, name="roberta")
        self.lm_head = TFRobertaLMHead(config, input_embeddings=self.roberta.embeddings, name="lm_head")