update app

app.py

@@ -6,11 +6,17 @@ 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)
+    outputs = model.generate(input_ids, max_length=200)
     edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return edited_text
 
 with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # Flip Text!
+    Start typing below to see the output.
+    """
+    )
     #設定輸入元件
     sent = gr.Textbox(label="Sentence")
     # 設定輸出元件