all add

app.py

@@ -14,20 +14,20 @@ model = AutoModelForSequenceClassification.from_pretrained(
     num_labels= 15,
     problem_type="multi_label_classification"
 )
-config = AutoConfig.from_pretrained(MODEL_NAME)
+# config = AutoConfig.from_pretrained(MODEL_NAME)
 
 MODEL_BUF = {
     "name": MODEL_NAME,
     "tokenizer": tokenizer,
     "model": model,
-    "config": config
+    # "config": config
 }
 
 def change_model_name(name):
     MODEL_BUF["name"] = name
     MODEL_BUF["tokenizer"] = AutoTokenizer.from_pretrained(name)
     MODEL_BUF["model"] = AutoModelForSequenceClassification.from_pretrained(name)
-    MODEL_BUF["config"] = AutoConfig.from_pretrained(name)
+    # MODEL_BUF["config"] = AutoConfig.from_pretrained(name)
 
 
 def predict(model_name, text):
@@ -36,7 +36,7 @@ def predict(model_name, text):
     
     tokenizer = MODEL_BUF["tokenizer"]
     model = MODEL_BUF["model"]
-    config = MODEL_BUF["config"]
+    # config = MODEL_BUF["config"]
 
     unsmile_labels = ["여성/가족","남성","성소수자","인종/국적","연령","지역","종교","기타 혐오","악플/욕설","clean", 'name', 'number', 'address', 'bank', 'person']
     num_labels = len(unsmile_labels)