src/transformers/models/xlm_roberta/modeling_xlm_roberta.py/XLMRobertaForCausalLM/__init__
class XLMRobertaForCausalLM:    def __init__(self, config):
        super().__init__(config)

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

        self.roberta = XLMRobertaModel(config, add_pooling_layer=False)
        self.lm_head = XLMRobertaLMHead(config)

        # The LM head weights require special treatment only when they are tied with the word embeddings
        self.update_keys_to_ignore(config, ["lm_head.decoder.weight"])

        # Initialize weights and apply final processing
        self.post_init()