add app

app.py

@@ -64,26 +64,16 @@ if __name__ == '__main__':
         "momo/KcBERT-base_Hate_speech_Privacy_Detection",
     ]
 
-    # #Create a gradio app with a button that calls predict()
-    # app = gr.Interface(
-    #     fn=predict,
-    #     inputs=[gr.inputs.Dropdown(model_name_list, label="Model Name"), 'text'], outputs=['label'], 
-    #     examples = [[MODEL_BUF["name"], text], [MODEL_BUF["name"], "4=🦀 4≠🦀"]],
-    #     title="한국어 혐오표현, 개인정보 판별기 (Korean Hate Speech and Privacy Detection)",
-    #     description="Korean Hate Speech and Privacy Detection."
-    #     )
-    # app.launch()
-
-
-    pipe = TextClassificationPipeline(
-    model = model,
-    tokenizer = tokenizer,
-    return_all_scores=True,
-    function_to_apply='sigmoid'
-    )
+    #Create a gradio app with a button that calls predict()
+    app = gr.Interface(
+        fn=predict,
+        inputs=[gr.inputs.Dropdown(model_name_list, label="Model Name"), 'text'], outputs=['label'], 
+        examples = [[MODEL_BUF["name"], text], [MODEL_BUF["name"], "4=🦀 4≠🦀"]],
+        title="한국어 혐오표현, 개인정보 판별기 (Korean Hate Speech and Privacy Detection)",
+        description="Korean Hate Speech and Privacy Detection."
+        )
+    app.launch()
     
-    gr.Interface.from_pipeline(pipe).launch()
-
 
 # # global var
 # MODEL_NAME = 'jason9693/SoongsilBERT-base-beep'