diff --git a/pipelines/bria/bria_pipeline.py b/pipelines/bria/bria_pipeline.py
index beec4e2dc..6049e3f45 100644
--- a/pipelines/bria/bria_pipeline.py
+++ b/pipelines/bria/bria_pipeline.py
@@ -237,11 +237,11 @@ class BriaPipeline(FluxPipeline):
     @replace_example_docstring(EXAMPLE_DOC_STRING)
     def __call__(
         self,
-        prompt: Union[str, List[str]] = None,
+        prompt: Union[str, List[str]] | None = None,
         height: Optional[int] = None,
         width: Optional[int] = None,
         num_inference_steps: int = 30,
-        timesteps: List[int] = None,
+        timesteps: List[int] | None = None,
         guidance_scale: float = 5,
         negative_prompt: Optional[Union[str, List[str]]] = None,
         num_images_per_prompt: Optional[int] = 1,
diff --git a/pipelines/bria/bria_utils.py b/pipelines/bria/bria_utils.py
index 3cddeafa1..5aed654c2 100644
--- a/pipelines/bria/bria_utils.py
+++ b/pipelines/bria/bria_utils.py
@@ -99,7 +99,7 @@ def get_by_t5_prompt_embeds(
 def get_t5_prompt_embeds(
     tokenizer: T5TokenizerFast ,
     text_encoder: T5EncoderModel,
-    prompt: Union[str, List[str]] = None,
+    prompt: Union[str, List[str]] | None = None,
     num_images_per_prompt: int = 1,
     max_sequence_length: int = 128,
     device: Optional[torch.device] = None,
@@ -184,7 +184,7 @@ def get_env_prefix():
 
 
 def compute_density_for_timestep_sampling(
-    weighting_scheme: str, batch_size: int, logit_mean: float = None, logit_std: float = None, mode_scale: float = None
+    weighting_scheme: str, batch_size: int, logit_mean: float | None = None, logit_std: float | None = None, mode_scale: float | None = None
 ):
     """Compute the density for sampling the timesteps when doing SD3 training.
 
@@ -236,7 +236,7 @@ def get_clip_prompt_embeds(
     text_encoder_2: CLIPTextModelWithProjection,
     tokenizer: CLIPTokenizer,
     tokenizer_2: CLIPTokenizer,
-    prompt: Union[str, List[str]] = None,
+    prompt: Union[str, List[str]] | None = None,
     num_images_per_prompt: int = 1,
     max_sequence_length: int = 77,
     device: Optional[torch.device] = None,
diff --git a/pipelines/bria/transformer_bria.py b/pipelines/bria/transformer_bria.py
index f75cde912..1378a8e16 100644
--- a/pipelines/bria/transformer_bria.py
+++ b/pipelines/bria/transformer_bria.py
@@ -82,7 +82,7 @@ class BriaTransformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, FromOrig
         attention_head_dim: int = 128,
         num_attention_heads: int = 24,
         joint_attention_dim: int = 4096,
-        pooled_projection_dim: int = None,
+        pooled_projection_dim: int | None = None,
         guidance_embeds: bool = False,
         axes_dims_rope: List[int] = [16, 56, 56],
         rope_theta = 10000,
diff --git a/pipelines/flex2/__init__.py b/pipelines/flex2/__init__.py
index dbb8e2a0d..1ba0a2eba 100644
--- a/pipelines/flex2/__init__.py
+++ b/pipelines/flex2/__init__.py
@@ -60,7 +60,7 @@ class Flex2Pipeline(FluxControlPipeline):
     @torch.no_grad()
     def __call__(
         self,
-        prompt: Union[str, List[str]] = None,
+        prompt: Union[str, List[str]] | None = None,
         prompt_2: Optional[Union[str, List[str]]] = None,
         inpaint_image: Optional[PipelineImageInput] = None,
         inpaint_mask: Optional[PipelineImageInput] = None,
diff --git a/pipelines/hidream/pipeline_hidream_image_editing.py b/pipelines/hidream/pipeline_hidream_image_editing.py
index c410ec8ac..09cdc4b26 100644
--- a/pipelines/hidream/pipeline_hidream_image_editing.py
+++ b/pipelines/hidream/pipeline_hidream_image_editing.py
@@ -210,7 +210,7 @@ class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoaderMixin
 
     def _get_t5_prompt_embeds(
         self,
-        prompt: Union[str, List[str]] = None,
+        prompt: Union[str, List[str]] | None = None,
         max_sequence_length: int = 128,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
@@ -284,7 +284,7 @@ class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoaderMixin
 
     def _get_llama3_prompt_embeds(
         self,
-        prompt: Union[str, List[str]] = None,
+        prompt: Union[str, List[str]] | None = None,
         max_sequence_length: int = 128,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
@@ -760,7 +760,7 @@ class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoaderMixin
     @replace_example_docstring(EXAMPLE_DOC_STRING)
     def __call__(
         self,
-        prompt: Union[str, List[str]] = None,
+        prompt: Union[str, List[str]] | None = None,
         prompt_2: Optional[Union[str, List[str]]] = None,
         prompt_3: Optional[Union[str, List[str]]] = None,
         prompt_4: Optional[Union[str, List[str]]] = None,
diff --git a/pipelines/model_hyimage.py b/pipelines/model_hyimage.py
index 307b31d58..4cf9776ee 100644
--- a/pipelines/model_hyimage.py
+++ b/pipelines/model_hyimage.py
@@ -81,8 +81,8 @@ class HunyuanImage3Wrapper(torch.nn.Module):
     def __call__(
         self,
         prompt: str,
-        height: int = None,
-        width: int = None,
+        height: int | None = None,
+        width: int | None = None,
         num_inference_steps: int = 50,
         num_images_per_prompt: int = 1,
         guidance_scale: float = 7.5,
diff --git a/pipelines/wan/wan_image.py b/pipelines/wan/wan_image.py
index bd9923e5b..254ed2fba 100644
--- a/pipelines/wan/wan_image.py
+++ b/pipelines/wan/wan_image.py
@@ -10,8 +10,8 @@ from modules import devices
 class WanImagePipeline(diffusers.WanPipeline):
     def __call__(
         self,
-        prompt: Union[str, List[str]] = None,
-        negative_prompt: Union[str, List[str]] = None,
+        prompt: Union[str, List[str]] | None = None,
+        negative_prompt: Union[str, List[str]] | None = None,
         height: int = 480,
         width: int = 832,
         num_frames: int = 81,