Auth

diarization.py

@@ -8,8 +8,8 @@ def perform_diarization(audio_file_path, translated_file_path, output_dir='./aud
 
     # Initialize diarization pipeline
     accesstoken = os.environ['Diarization']
-    pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1", token=accesstoken )
-    
+    pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1", use_auth_token=accesstoken )
+
     # Send pipeline to GPU (when available)
     pipeline.to(torch.device("cuda" if torch.cuda.is_available() else "cpu"))