diff --git a/modelscope/pipelines/multi_modal/efficient_diffusion_tuning_pipeline.py b/modelscope/pipelines/multi_modal/efficient_diffusion_tuning_pipeline.py
index 1b791634..320d83e7 100644
--- a/modelscope/pipelines/multi_modal/efficient_diffusion_tuning_pipeline.py
+++ b/modelscope/pipelines/multi_modal/efficient_diffusion_tuning_pipeline.py
@@ -36,8 +36,10 @@ class EfficientDiffusionTuningPipeline(Pipeline):
                 'data/test/images/vision_efficient_tuning_test_1.png')
             >>> print(f'Output: {result}.')
         """
+        logger.warn(
+            '[NOTE]Do not use this pipeline because the dependencies are too old, '
+            'use https://github.com/modelscope/DiffSynth-Studio instead')
         super().__init__(model=model, **kwargs)
-
         self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
         self.model = self.model.to(self.device)
         self.model.eval()
diff --git a/tests/pipelines/test_efficient_diffusion_tuning.py b/tests/pipelines/test_efficient_diffusion_tuning.py
index 1f224917..af52d65f 100644
--- a/tests/pipelines/test_efficient_diffusion_tuning.py
+++ b/tests/pipelines/test_efficient_diffusion_tuning.py
@@ -11,10 +11,10 @@ from modelscope.utils.test_utils import test_level
 class EfficientDiffusionTuningTest(unittest.TestCase):
 
     def setUp(self) -> None:
-        os.system('pip install ms-swift -U')
+        # os.system('pip install ms-swift -U')
         self.task = Tasks.efficient_diffusion_tuning
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skip
     def test_efficient_diffusion_tuning_lora_run_pipeline(self):
         model_id = 'damo/multi-modal_efficient-diffusion-tuning-lora'
         model_revision = 'v1.0.2'
@@ -24,7 +24,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
         result = edt_pipeline(inputs)
         print(f'Efficient-diffusion-tuning-lora output: {result}.')
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skip
     def test_efficient_diffusion_tuning_lora_load_model_from_pretrained(self):
         model_id = 'damo/multi-modal_efficient-diffusion-tuning-lora'
         model_revision = 'v1.0.2'
@@ -32,7 +32,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
         from modelscope.models.multi_modal import EfficientStableDiffusion
         self.assertTrue(model.__class__ == EfficientStableDiffusion)
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skip
     def test_efficient_diffusion_tuning_control_lora_run_pipeline(self):
         # TODO: to be fixed in the future
         model_id = 'damo/multi-modal_efficient-diffusion-tuning-control-lora'
@@ -48,7 +48,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
         result = edt_pipeline(inputs)
         print(f'Efficient-diffusion-tuning-control-lora output: {result}.')
 
-    @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
+    @unittest.skip
     def test_efficient_diffusion_tuning_control_lora_load_model_from_pretrained(
             self):
         model_id = 'damo/multi-modal_efficient-diffusion-tuning-control-lora'