Update app.py

app.py

@@ -5,6 +5,9 @@ from datasets import load_dataset
 
 from transformers import SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Processor, pipeline
 
+from transformers import M2M100ForConditionalGeneration
+from small100.tokenization_small100 import SMALL100Tokenizer
+
 
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
@@ -13,9 +16,6 @@ device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
 asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=device, generate_kwargs = {"task": "translate"})
 
-from transformers import M2M100ForConditionalGeneration
-from tokenization_small100 import SMALL100Tokenizer
-
 model = M2M100ForConditionalGeneration.from_pretrained("alirezamsh/small100")
 tokenizer = M2M100Tokenizer.from_pretrained("alirezamsh/small100", tgt_lang="sw")