diff --git a/src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py b/src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py
index a4f3788fa6..2228649eb5 100644
--- a/src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py
+++ b/src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py
@@ -1317,7 +1317,7 @@ class UniDiffuserPipeline(DiffusionPipeline):
             latents = self._combine(image_vae_latents, image_clip_latents)
         elif mode in ["img2text", "text"]:
             latents = prompt_embeds
-        
+
         print(f"Initial latents: {latents}")
 
         # 7. Check that shapes of latents and image match the UNet channels.
diff --git a/tests/pipelines/unidiffuser/test_unidiffuser.py b/tests/pipelines/unidiffuser/test_unidiffuser.py
index b0a189fbf2..e7834c61a0 100644
--- a/tests/pipelines/unidiffuser/test_unidiffuser.py
+++ b/tests/pipelines/unidiffuser/test_unidiffuser.py
@@ -589,10 +589,9 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase):
 
         expected_text_prefix = "Astronaut "
         assert text[0][:10] == expected_text_prefix
-    
+
     def test_unidiffuser_default_joint_v1_fp16(self):
         pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers", torch_dtype=torch.float16)
-        pipe.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/home/tamamo/scratch/unidiffuser_big/image_encoder")
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -613,10 +612,9 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase):
 
         expected_text_prefix = "Pink pink "
         assert text[0][:10] == expected_text_prefix
-    
+
     def test_unidiffuser_default_text2img_v1_fp16(self):
         pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers", torch_dtype=torch.float16)
-        pipe.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/home/tamamo/scratch/unidiffuser_big/image_encoder")
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -630,10 +628,9 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase):
         image_slice = image[0, -3:, -3:, -1]
         expected_slice = np.array([0.4702, 0.4666, 0.4446, 0.4829, 0.4468, 0.4565, 0.4663, 0.4956, 0.4277])
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-    
+
     def test_unidiffuser_default_text2img_v1_fp16_no_cfg(self):
         pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers", torch_dtype=torch.float16)
-        pipe.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/home/tamamo/scratch/unidiffuser_big/image_encoder")
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -651,7 +648,6 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase):
 
     def test_unidiffuser_default_img2text_v1_fp16(self):
         pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers", torch_dtype=torch.float16)
-        pipe.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/home/tamamo/scratch/unidiffuser_big/image_encoder")
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -663,4 +659,3 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase):
 
         expected_text_prefix = "Astronaut "
         assert text[0][:10] == expected_text_prefix
-