def METHOD_NAME(self):
    model_meta_data = ModelMetadata(
        name="model_for_deci_lab_upload_test",
        primary_batch_size=1,
        architecture="Resnet18",
        framework="pytorch",
        dl_task="classification",
        input_dimensions=(3, 224, 224),
        primary_hardware="XEON",
        dataset_name="imagenet",
        description="ResNet18 ONNX deci.ai Test",
        tags=["imagenet", "resnet18"],
    )
    optimization_request_form = OptimizationRequestForm(
        target_hardware="XEON",
        target_batch_size=1,
        target_metric=Metric.LATENCY,
        optimize_model_size=True,
        quantization_level=QuantizationLevel.FP16,
        optimize_autonac=True,
    )
    model_conversion_callback = ModelConversionCheckCallback(model_meta_data=model_meta_data)
    deci_lab_callback = DeciLabUploadCallback(model_meta_data=model_meta_data, optimization_request_form=optimization_request_form)
    net = ResNet18(num_classes=5, arch_params={})
    train_params = {
        "max_epochs": 2,
        "lr_updates": [1],
        "lr_decay_factor": 0.1,
        "lr_mode": "step",
        "lr_warmup_epochs": 0,
        "initial_lr": 0.1,
        "loss": "cross_entropy",
        "optimizer": self.optimizer,
        "criterion_params": {},
        "train_metrics_list": [Accuracy(), Top5()],
        "valid_metrics_list": [Accuracy(), Top5()],
        "metric_to_watch": "Accuracy",
        "greater_metric_to_watch_is_better": True,
        "phase_callbacks": [model_conversion_callback, deci_lab_callback],
    }
    self.optimizer = SGD(params=net.parameters(), lr=0.1)
    self.trainer.train(
        model=net, training_params=train_params, train_loader=classification_test_dataloader(), valid_loader=classification_test_dataloader()
    )
    # CLEANUP
    # FIXME: MISUSE OF DECI_PLATFROM CALLBACK:
    #  https://github.com/Deci-AI/deci_trainer/pull/106/files/2ed12b78adc9886faabad9d952969ff5479e9237#r708092979
    new_model_from_repo_name = model_meta_data.name + "_1_1"
    your_model_from_repo = deci_lab_callback.platform_client.get_model_by_name(name=new_model_from_repo_name).data
    deci_lab_callback.platform_client.delete_model(your_model_from_repo.model_id)