def load_checkpoint_from_config(self, cfg, **kwargs):
        """
        Load checkpoint as specified in the config file.

        If load_finetuned is True, load the finetuned model; otherwise, load the pretrained model.
        When loading the pretrained model, each task-specific architecture may define their
        own load_from_pretrained() method.
        """
        load_finetuned = cfg.get("load_finetuned", True)
        if load_finetuned:
            finetune_path = cfg.get("finetuned", None)
            assert (
                finetune_path is not None
            ), "Found load_finetuned is True, but finetune_path is None."
            self.load_checkpoint(url_or_filename=finetune_path)
        else:
            # load pre-trained weights
            pretrain_path = cfg.get("pretrained", None)
            assert "Found load_finetuned is False, but pretrain_path is None."
            self.load_from_pretrained(url_or_filename=pretrain_path, **kwargs)

        Load checkpoint as specified in the config file.

        If load_finetuned is True, load the finetuned model; otherwise, load the pretrained model.
        When loading the pretrained model, each task-specific architecture may define their
        own load_from_pretrained() method.
        
video_chat_text/video_miniGPT4/minigpt4/models/base_model.py