Update app.py

app.py

@@ -3,16 +3,16 @@ import numpy as np
 import torch
 from datasets import load_dataset
 
-from transformers import SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Processor, pipeline
-
+from transformers import SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Processor, pipeline, WhisperTokenizer
 
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
-
+tokenizer = WhisperTokenizer.from_pretrained("GatinhoEducado/whisper-tiny-finetuned-minds14", language="Portuguese", task="translate")
 # load speech translation checkpoint
 asr_pipe = pipeline(
     "automatic-speech-recognition", 
     model="GatinhoEducado/whisper-tiny-finetuned-minds14",
     device=device,
+    tokenizer = tokenizer,
     generate_kwargs = {"language":"<|pt|>",
                      "task": "transcribe",
                      "repetition_penalty":1.5