Update demo.py

demo.py

@@ -43,11 +43,6 @@ css = """
     margin: 0 5px;
     color: black;
 }
-.row {
-    display: flex;
-    justify-content: center;
-    width: 100%;
-}
 """
 
 # Gradio App
@@ -55,15 +50,17 @@ with gr.Blocks(css=css) as app:
     with gr.Row():
         gr.HTML('<div id="header">R-detect On HuggingFace</div>')
     with gr.Row():
-        gr.HTML("""
-        <div class="links">
-            <a href="https://openreview.net/forum?id=z9j7wctoGV" target="_blank">Paper</a>
-            <span class="separator">|</span>
-            <a href="https://github.com/xLearn-AU/R-Detect" target="_blank">Code</a>
-            <span class="separator">|</span>
-            <a href="mailto:[email protected]" target="_blank">Contact</a>
-        </div>
-        """)
+        gr.HTML(
+            """
+            <div class="links">
+                <a href="https://openreview.net/forum?id=z9j7wctoGV" target="_blank">Paper</a>
+                <span class="separator">|</span>
+                <a href="https://github.com/xLearn-AU/R-Detect" target="_blank">Code</a>
+                <span class="separator">|</span>
+                <a href="mailto:[email protected]" target="_blank">Contact</a>
+            </div>
+            """
+        )
     with gr.Row():
         input_text = gr.Textbox(
             label="Input Text",
@@ -72,7 +69,7 @@ with gr.Blocks(css=css) as app:
         )
         output = gr.Textbox(
             label="Inference Result",
-            placeholder="Made by Human or AI",
+            placeholder="Maked by Human or AI",
             elem_id="output-text",
         )
     with gr.Row():
@@ -87,27 +84,31 @@ with gr.Blocks(css=css) as app:
         )
         submit_button = gr.Button("Run Detection", variant="primary")
         clear_button = gr.Button("Clear", variant="secondary")
+
     
-    # Hooking up the change_mode function to select different models
     submit_button.click(run_test_power, inputs=[model_name, input_text, input_text], outputs=output)
     clear_button.click(lambda: ("", ""), inputs=[], outputs=[input_text, output])
+#    model_name.change(change_mode, inputs=[model_name], outputs=[model_name])
 
     with gr.Accordion("Disclaimer", open=False):
-        gr.Markdown("""
-        - **Disclaimer**: This tool is for demonstration purposes only. It is not a foolproof AI detector.
-        - **Accuracy**: Results may vary based on input length and quality.
-        """)
-
+        gr.Markdown(
+            """
+            - **Disclaimer**: This tool is for demonstration purposes only. It is not a foolproof AI detector.
+            - **Accuracy**: Results may vary based on input length and quality.
+            """
+        )
     with gr.Accordion("Citations", open=False):
-        gr.Markdown("""
-        ```
-        @inproceedings{zhangs2024MMDMP,
-            title={Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy},
-            author={Zhang, Shuhai and Song, Yiliao and Yang, Jiahao and Li, Yuanqing and Han, Bo and Tan, Mingkui},
-            booktitle = {International Conference on Learning Representations (ICLR)},
-            year={2024}
-        }
-        ```
-        """)
+        gr.Markdown(
+            """
+            ```
+            @inproceedings{zhangs2024MMDMP,
+                title={Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy},
+                author={Zhang, Shuhai and Song, Yiliao and Yang, Jiahao and Li, Yuanqing and Han, Bo and Tan, Mingkui},
+                booktitle = {International Conference on Learning Representations (ICLR)},
+                year={2024}
+            }
+            ```
+            """
+        )
 
 app.launch()