Update app.py

removed .to(device) from tokeniser and added to synthesise()

app.py

@@ -15,7 +15,7 @@ asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base",
 #processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
 
 model = VitsModel.from_pretrained("Matthijs/mms-tts-fra").to(device)
-tokenizer = VitsTokenizer.from_pretrained("Matthijs/mms-tts-fra").to(device)
+tokenizer = VitsTokenizer.from_pretrained("Matthijs/mms-tts-fra")
 
 #embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
 #speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
@@ -30,7 +30,7 @@ def synthesise(text):
     #inputs = processor(text=text, return_tensors="pt")
     #speech = model.generate_speech(inputs["input_ids"].to(device), speaker_embeddings.to(device), vocoder=vocoder)
     inputs = tokenizer(text_example, return_tensors="pt")
-    input_ids = inputs["input_ids"]
+    input_ids = inputs["input_ids"].to(device)
 
 
     with torch.no_grad():