add row

app.py

@@ -107,26 +107,27 @@ Note: in case the model to convert is larger than 2 GB, it will be saved in a su
 """
 
 with gr.Blocks() as demo:
-    with gr.Column(scale=50):
-        gr.HTML(TTILE_IMAGE)
-        gr.HTML(TITLE)
-        gr.Markdown(DESCRIPTION)
-
-    with gr.Column(scale=50):
-        input_token = gr.Textbox(max_lines=1, label="Hugging Face token")
-        input_model = gr.Textbox(
-            max_lines=1,
-            label="Model name",
-            placeholder="textattack/distilbert-base-cased-CoLA",
-        )
-        input_task = gr.Textbox(
-            value="auto",
-            max_lines=1,
-            label='Task (can be left to "auto", will be automatically inferred)',
-        )
-
-        btn = gr.Button("Convert to ONNX")
-        output = gr.Markdown(label="Output")
+    with gr.Row():
+        with gr.Column(scale=50):
+            gr.HTML(TTILE_IMAGE)
+            gr.HTML(TITLE)
+            gr.Markdown(DESCRIPTION)
+
+        with gr.Column(scale=50):
+            input_token = gr.Textbox(max_lines=1, label="Hugging Face token")
+            input_model = gr.Textbox(
+                max_lines=1,
+                label="Model name",
+                placeholder="textattack/distilbert-base-cased-CoLA",
+            )
+            input_task = gr.Textbox(
+                value="auto",
+                max_lines=1,
+                label='Task (can be left to "auto", will be automatically inferred)',
+            )
+
+            btn = gr.Button("Convert to ONNX")
+            output = gr.Markdown(label="Output")
 
     btn.click(
         fn=onnx_export, inputs=[input_token, input_model, input_task], outputs=output