load a checkpoint that has jpn config

app.py

@@ -11,9 +11,9 @@ device = "cuda:0" if torch.cuda.is_available() else "cpu"
 # load speech translation checkpoint
 asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=device)
 
-# load text-to-speech checkpoint and speaker embeddings
-model = VitsModel.from_pretrained("facebook/mms-tts")
-tokenizer = VitsTokenizer.from_pretrained("facebook/mms-tts")
+# load MMS VITS model
+model = VitsModel.from_pretrained("mms-1b-fl102")
+tokenizer = VitsTokenizer.from_pretrained("mms-1b-fl102")
 
 embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
 speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)