Update app.py

app.py

@@ -19,16 +19,14 @@ whisper_model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-
 forced_decoder_ids = tokenizer.get_decoder_prompt_ids(language="french", task="translate")
 
 #load text-to-speech checkpoint and speaker embeddings
-processor = SpeechT5Processor.from_pretrained("leo-kwan/speecht5_finetuned_voxpopuli_lt")
+processor = SpeechT5Processor.from_pretrained("Apocalypse-19/speecht5_finetuned_french")
 
-model = SpeechT5ForTextToSpeech.from_pretrained("leo-kwan/speecht5_finetuned_voxpopuli_lt").to(device)
+model = SpeechT5ForTextToSpeech.from_pretrained("Apocalypse-19/speecht5_finetuned_french").to(device)
 vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan").to(device)
 
 embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
 speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
 
-# bark_model = BarkModel.from_pretrained("suno/bark-small")
-# processor = BarkProcessor.from_pretrained("suno/bark-small")
 
 def translate(audio):
     # load speech translation checkpoint