update init app.

app.py

@@ -3,15 +3,13 @@ import operator
 import torch
 from transformers import BertTokenizer, BertForMaskedLM
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 tokenizer = BertTokenizer.from_pretrained("shibing624/macbert4csc-base-chinese")
 model = BertForMaskedLM.from_pretrained("shibing624/macbert4csc-base-chinese")
-model.to(device)
 
 
 def ai_text(texts):
     with torch.no_grad():
-        outputs = model(**tokenizer(texts, padding=True, return_tensors='pt').to(device))
+        outputs = model(**tokenizer(texts, padding=True, return_tensors='pt'))
 
     def get_errors(corrected_text, origin_text):
         sub_details = []
@@ -42,12 +40,14 @@ def ai_text(texts):
     return result
 
 
+print(ai_text(['少先队员因该为老人让坐']))
+
 examples = [
     ['真麻烦你了。希望你们好好的跳无'],
     ['少先队员因该为老人让坐'],
     ['机七学习是人工智能领遇最能体现智能的一个分知'],
-    ['今天心情很好',
-     '老是较书。'],
+    ['今天心情很好'],
+    ['老是较书。'],
     ['遇到一位很棒的奴生跟我聊天。'],
     ['他的语说的很好，法语也不错'],
     ['他法语说的很好，的语也不错'],
@@ -56,6 +56,6 @@ examples = [
 ]
 
 output_text = gr.outputs.Textbox()
-gr.Interface(ai_text, "textbox", output_text, title="Chinese Text Correction shibing624/macbert4csc-base-chinese",
+gr.Interface(ai_text, "text", "text", title="Chinese Text Correction shibing624/macbert4csc-base-chinese",
              description="Copy or input error Chinese text. Submit and the machine will correct text.",
              examples=examples).launch()