update app

app.py

@@ -5,8 +5,8 @@ model = T5ForConditionalGeneration.from_pretrained("CodeTed/traditional_CSC_t5")
 
 
 def cged_correction(sentence = '為了降低少子化，政府可以堆動獎勵生育的政策。'):
-    input_ids = tokenizer('糾正句子裡的錯字：' + sentence + '_輸出句：', return_tensors="pt").input_ids
-    outputs = model.generate(input_ids, max_length=256)
+    input_ids = tokenizer('糾正句子裡的錯字：' + sentence, return_tensors="pt").input_ids
+    outputs = model.generate(input_ids, max_length=200)
     edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return edited_text