Marian didn't work, rolled back version to autotokenizer

app.py

@@ -1,18 +1,19 @@
 from pypinyin import pinyin
-from transformers import MarianMTModel, MarianTokenizer
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from LAC import LAC
 import gradio as gr
 import torch
 
-model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
+model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
 model.eval()
-tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
+tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
 lac = LAC(mode="seg")
 
 def make_request(chinese_text):
   with torch.no_grad():
-      generated_tokens = model.generate(**tokenizer(chinese_text, return_tensors="pt", padding=True))
-      return [tokenizer.decode(generated_tokens, skip_special_tokens=True) for t in generated_tokens]
+      encoded_zh = tokenizer.prepare_seq2seq_batch([chinese_text], return_tensors="pt")
+      generated_tokens = model.generate(**encoded_zh)
+      return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
 
 def generatepinyin(input):
   pinyin_list = pinyin(input)