Update app.py

app.py

@@ -14,14 +14,15 @@ token_key = os.environ.get("HUGGING_FACE_HUB_TOKEN")
 #model_name = "unilux/wav2vec-xls-r-Luxembourgish20-with-LM"
 #model_name = "unilux/wav2vec-xlsr-300m-Luxembourgish-with-LM"
 model_name = "pgilles/whisper-large-lb"
-tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(model_name, use_auth_token=token_key)
-model = Wav2Vec2ForCTC.from_pretrained(model_name, use_auth_token=token_key)
-processor = Wav2Vec2ProcessorWithLM.from_pretrained(model_name, use_auth_token=token_key)
+#tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(model_name, use_auth_token=token_key)
+#model = Wav2Vec2ForCTC.from_pretrained(model_name, use_auth_token=token_key)
+#processor = Wav2Vec2ProcessorWithLM.from_pretrained(model_name, use_auth_token=token_key)
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model = model.to(device)
 
-p = pipeline("automatic-speech-recognition", model=model, tokenizer=tokenizer, feature_extractor=processor.feature_extractor, decoder=processor.decoder, use_auth_token=token_key)
+#p = pipeline("automatic-speech-recognition", model=model, tokenizer=tokenizer, feature_extractor=processor.feature_extractor, decoder=processor.decoder, use_auth_token=token_key)
+p = pipeline("automatic-speech-recognition", model=model, use_auth_token=token_key)
 
 #p = pipeline("automatic-speech-recognition", model=model_name, use_auth_token = token_key)
 #p = pipeline("automatic-speech-recognition", model=model_name, use_auth_token = True)