hopefully better style

app.py

@@ -60,7 +60,11 @@ DESCRIPTION = """
     <img src="https://huggingface.co/spaces/optimum/exporters/resolve/main/clean_hf_onnx.png"/>
 </p>
 
-This Space allows to automatically convert to ONNX transformers models hosted on the Hugging Face Hub. It opens a PR on the target model, and it is up to the owner of the original model
+<p align="center">
+    # Convert any PyTorch model to ONNX with 🤗 Optimum exporters 🏎️
+</p>
+
+This Space allows to automatically convert to ONNX 🤗 transformers models hosted on the Hugging Face Hub. It opens a PR on the target model, and it is up to the owner of the original model
 to merge the PR to allow people to leverage the ONNX standard to share and use the model on a wide range of devices!
 
 Once converted, the model can for example be used in the [🤗 Optimum](https://huggingface.co/docs/optimum/) library following closely the transormers API.
@@ -76,11 +80,24 @@ The steps are the following:
 Note: in case the model to convert is larger than 2 GB, it will be saved in a subfolder called `onnx/`. To load it from Optimum, the argument `subfolder="onnx"` should be provided.
 """
 
+with gr.Blocks() as demo:
+    gr.Markdown(DESCRIPTION)
+
+    with gr.Row():
+        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 blank, will be automatically inferred)")
+        output = gr.Markdown(label="Output")
+    
+    btn = gr.Button("Convert to ONNX")
+    btn.click(fn=onnx_export, inputs=[input_token, input_model, input_task], outputs=output)
+
+"""
 demo = gr.Interface(
-    title="Convert any PyTorch model to ONNX with 🤗 Optimum Exporters 🏎️",
+    title="",
     description=DESCRIPTION,
     allow_flagging="never",
-    article="Check out the [Optimum repo on GitHub](https://github.com/huggingface/optimum)",
+    article="Check out the [🤗 Optimum repoository on GitHub](https://github.com/huggingface/optimum) as well!",
     inputs=[
         gr.Text(max_lines=1, label="Hugging Face token"),
         gr.Text(max_lines=1, label="Model name", placeholder="textattack/distilbert-base-cased-CoLA"),
@@ -89,5 +106,6 @@ demo = gr.Interface(
     outputs=[gr.Markdown(label="output")],
     fn=onnx_export,
 )
+"""
 
 demo.launch()