update app.py

app.py

@@ -1,6 +1,14 @@
 import gradio as gr
-def cged_correction(sentence):
-    return sentence
+from transformers import AutoTokenizer, T5ForConditionalGeneration
+tokenizer = AutoTokenizer.from_pretrained("CodeTed/traditional_CSC_t5")
+model = T5ForConditionalGeneration.from_pretrained("CodeTed/traditional_CSC_t5")
+
+
+def cged_correction(sentence = '糾正句子裡的錯字: 為了降低少子化，政府可以堆動獎勵生育的政策。'):
+    input_ids = tokenizer(sentence, return_tensors="pt").input_ids
+    outputs = model.generate(input_ids, max_length=256)
+    edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return edited_text
 
 with gr.Blocks() as demo:
     #設定輸入元件