src/transformers/models/xglm/modeling_tf_xglm.py/TFXGLMForCausalLM/__init__
class TFXGLMForCausalLM:    def __init__(
        self, config: XGLMConfig, embed_tokens: Optional[TFSharedEmbeddings] = None, *inputs: Any, **kwargs: Any
    ) -> None:
        super().__init__(config, *inputs, **kwargs)

        self.model = TFXGLMMainLayer(config, embed_tokens=embed_tokens, name="model")
        self.lm_head = tf.keras.layers.Dense(
            config.vocab_size,
            use_bias=False,
            kernel_initializer=get_initializer(config.init_std),
            name="lm_head",
        )

        # TODO (Joao): investigate why XGLM has numerical issues in XLA generate
        self.supports_xla_generation = False