def METHOD_NAME(self):
    with tempfile.TemporaryFile() as fp:
        with init_empty_weights_with_disk_offload(ignore_tie_weights=True):
            model = MyModel(5, self.embed_dim)
            torch.save(model.state_dict(), fp)
        fp.seek(0)
        sd = torch.load(fp, map_location="cpu")
        model.load_state_dict(sd)
    device2name = defaultdict(list)
    for name, params in model.named_parameters():
        device2name[params.device].append(name)
    for name, params in model.named_parameters():
        self.assertTrue(params.device.type == "meta")
    # reload_meta_module(model, "cpu")