Update app.py

app.py

@@ -21,8 +21,8 @@ from transformers.pipelines.audio_utils import ffmpeg_read
 HF_TOKEN = "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"
 # set up the diarization pipeline
 diarization_pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.0", use_auth_token=HF_TOKEN)
- if torch.cuda.is_available():
-        diarization_pipeline.to(torch.device("cuda"))
+if torch.cuda.is_available():
+    diarization_pipeline.to(torch.device("cuda"))
 
 def transcribe(audio_path, task="transcribe", group_by_speaker=True, progress=gr.Progress()):
     # # run Whisper JAX asynchronously using Gradio client (endpoint)