Update app.py

app.py

@@ -5,8 +5,8 @@ from datasets import load_dataset
 
 from transformers import SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Processor, pipeline
 
-from transformers import M2M100ForConditionalGeneration
-from tokenization_small100 import SMALL100Tokenizer
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+# from tokenization_small100 import SMALL100Tokenizer
 
 
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
@@ -16,10 +16,9 @@ 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"})
 
-model = M2M100ForConditionalGeneration.from_pretrained("alirezamsh/small100")
-tokenizer = SMALL100Tokenizer.from_pretrained("alirezamsh/small100", tgt_lang="sw")
-
 
+model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
+tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
 
 # load text-to-speech checkpoint and speaker embeddings
 # processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")