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README.md

@@ -13,7 +13,7 @@ This package provides an **Automatic Speech Recognition (ASR) + Speaker Diarizat
 
 ## Install
 ```bash
-pip install git+https://huggingface.co/Capstone04/asr-diarization-pipeline
+pip install git+https://huggingface.co/Capstone04/live-transcription-pipeline
 
 ## Speaker Identification
 You can now enroll known speakers by providing reference audio samples. The pipeline will match incoming speaker segments against stored embeddings and label them accordingly. Unknown speakers are dynamically tracked per session.

asr_diarization/pipeline.py

@@ -40,7 +40,10 @@ class ASR_Diarization:
             self.embedding_model = None
             print(f"[ERROR] Failed to load ECAPA: {e}")
 
-        self.diar_pipeline = Pipeline.from_pretrained(diar_model, use_auth_token=HF_TOKEN)
+        #self.diar_pipeline = Pipeline.from_pretrained(diar_model, use_auth_token=HF_TOKEN)
+        os.environ["HF_TOKEN"] = HF_TOKEN
+        os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
+        self.diar_pipeline = Pipeline.from_pretrained(diar_model)
         device_index = 0 if torch.cuda.is_available() else -1
         self.asr_pipeline = hf_pipeline(
             "automatic-speech-recognition",