diff --git a/fastvideo/pipelines/basic/minimax_h3/stages/minimax_h3_denoising.py b/fastvideo/pipelines/basic/minimax_h3/stages/minimax_h3_denoising.py
index 0f09d4a05..e03a87e58 100644
--- a/fastvideo/pipelines/basic/minimax_h3/stages/minimax_h3_denoising.py
+++ b/fastvideo/pipelines/basic/minimax_h3/stages/minimax_h3_denoising.py
@@ -6,7 +6,6 @@ from __future__ import annotations
 import contextlib
 from typing import Any
 
-
 import torch
 
 from fastvideo.distributed import get_local_torch_device
@@ -106,8 +105,8 @@ class MiniMaxH3DenoisingStage(PipelineStage):
                           if controller is not None else contextlib.nullcontext())
         try:
             with denoise_region:
-                for index, (video_timestep, audio_timestep) in enumerate(zip(video_timesteps, audio_timesteps,
-                                                                             strict=True)):
+                for index, (video_timestep,
+                            audio_timestep) in enumerate(zip(video_timesteps, audio_timesteps, strict=True)):
                     unique_timesteps, timestep_indices = row_timestep_plan[index]
                     # Under torch.compile(mode="reduce-overhead") each denoising
                     # step must be marked, or cudagraph trees flag cross-step
diff --git a/fastvideo/utils.py b/fastvideo/utils.py
index 76740f6dc..79757a23a 100644
--- a/fastvideo/utils.py
+++ b/fastvideo/utils.py
@@ -720,15 +720,11 @@ def maybe_download_model_index(model_name_or_path: str, revision: str | None = N
         config_filename = "model_index.json"
         try:
             filename = f"{subfolder}/{config_filename}" if subfolder else config_filename
-            model_index_path = hf_hub_download(repo_id=repo_id,
-                                               filename=filename,
-                                               revision=revision)
+            model_index_path = hf_hub_download(repo_id=repo_id, filename=filename, revision=revision)
         except EntryNotFoundError:
             config_filename = "modular_model_index.json"
             filename = f"{subfolder}/{config_filename}" if subfolder else config_filename
-            model_index_path = hf_hub_download(repo_id=repo_id,
-                                               filename=filename,
-                                               revision=revision)
+            model_index_path = hf_hub_download(repo_id=repo_id, filename=filename, revision=revision)
 
         # Load the selected manifest.
         with open(model_index_path) as f:
@@ -739,14 +735,12 @@ def maybe_download_model_index(model_name_or_path: str, revision: str | None = N
             raise ValueError(f"{config_filename} for {model_name_or_path} does not contain _class_name field")
 
         if "_diffusers_version" not in config:
-            raise ValueError(
-                f"{config_filename} for {model_name_or_path} does not contain _diffusers_version field")
+            raise ValueError(f"{config_filename} for {model_name_or_path} does not contain _diffusers_version field")
 
         # Add the pipeline name for downstream use
         config["pipeline_name"] = config["_class_name"]
 
-        logger.info("Downloaded %s for %s, pipeline: %s", config_filename, model_name_or_path,
-                    config["_class_name"])
+        logger.info("Downloaded %s for %s, pipeline: %s", config_filename, model_name_or_path, config["_class_name"])
         return config
 
     except Exception as e: