src/transformers/models/pegasus/modeling_pegasus.py/PegasusForConditionalGeneration/__init__
class PegasusForConditionalGeneration:    def __init__(self, config: PegasusConfig):
        super().__init__(config)
        self.model = PegasusModel(config)
        self.register_buffer("final_logits_bias", torch.zeros((1, self.model.shared.num_embeddings)))
        self.lm_head = nn.Linear(config.d_model, self.model.shared.num_embeddings, bias=False)

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