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asr_diarization/pipeline.py

@@ -21,12 +21,16 @@ class ASR_Diarization:
         # Load diarization model
         self.diar_pipeline = Pipeline.from_pretrained(diar_model, use_auth_token=HF_TOKEN)
 
-        # Load ASR model with timestamps
+        processor = WhisperProcessor.from_pretrained(asr_model, token=HF_TOKEN)
+        model = WhisperForConditionalGeneration.from_pretrained(asr_model, token=HF_TOKEN).to(self.device)
+
         self.asr_pipeline = hf_pipeline(
             "automatic-speech-recognition",
-            model=asr_model,
+            model=model,
+            tokenizer=processor.tokenizer,
+            feature_extractor=processor.feature_extractor,
             device=0 if self.device == "cuda" else -1,
-            return_timestamps=True,
+            return_timestamps=True
         )
 
     def run_diarization(self, audio_path):