def DPT_Next_ViT_L_384(pretrained=True, **kwargs):
    """ # This docstring shows up in hub.help()
    MiDaS DPT_Next_ViT_L_384 model for monocular depth estimation
    pretrained (bool): load pretrained weights into model
    """

    model = DPTDepthModel(
            path=None,
            backbone="next_vit_large_6m",
            non_negative=True,
        )

    if pretrained:
        checkpoint = (
            "https://github.com/isl-org/MiDaS/releases/download/v3_1/dpt_next_vit_large_384.pt"
        )
        state_dict = torch.hub.load_state_dict_from_url(
            checkpoint, map_location=torch.device('cpu'), progress=True, check_hash=True
        )
        model.load_state_dict(state_dict)

    return model
 # This docstring shows up in hub.help()
    MiDaS DPT_Next_ViT_L_384 model for monocular depth estimation
    pretrained (bool): load pretrained weights into model
    
ControlNet-v1-1-nightly/annotator/zoe/zoedepth/models/base_models/midas_repo/hubconf.py