:lipstick: improve and condense UI

app.py

@@ -163,56 +163,61 @@ if __name__ == "__main__":
 
             gr.Markdown("## Load Inputs & Select Parameters")
             gr.Markdown(
-                "Enter text below in the text area. The text will be summarized [using the selected parameters](https://huggingface.co/blog/how-to-generate). Optionally load an example from the list below or upload a file."
+                "Enter text below in the text area. The text will be summarized [using the selected parameters](https://huggingface.co/blog/how-to-generate). Optionally load an example below or upload a file."
             )
+            with gr.Row():
+                model_size = gr.Radio(
+                    choices=["base", "large"], label="model size", value="large"
+                )
+                num_beams = gr.Radio(
+                    choices=[2, 3, 4],
+                    label="num beams",
+                    value=2,
+                )
             gr.Markdown("_The base model is less performant than the large model, but is faster and will accept up to 2048 words per input (Large model accepts up to 768)._")
-            model_size = gr.Radio(
-                choices=["base", "large"], label="model size", value="large"
-            )
-            num_beams = gr.Radio(
-                choices=[2, 3, 4],
-                label="num beams",
-                value=2,
-            )
-            token_batch_length = gr.Radio(
-                choices=[512, 768, 1024],
-                label="token batch length",
-                value=512,
-            )
-            length_penalty = gr.inputs.Slider(
-                minimum=0.5, maximum=1.0, label="length penalty", default=0.7, step=0.05
-            )
-            repetition_penalty = gr.inputs.Slider(
-                minimum=1.0,
-                maximum=5.0,
-                label="repetition penalty",
-                default=3.5,
-                step=0.1,
-            )
-            no_repeat_ngram_size = gr.Radio(
-                choices=[2, 3, 4],
-                label="no repeat ngram size",
-                value=3,
-            )
-            example_name = gr.Dropdown(
-                list(name_to_path.keys()),
-                label="Choose an Example",
-            )
-            load_examples_button = gr.Button(
-                "Load Example",
-            )
+            with gr.Row():
+                token_batch_length = gr.Radio(
+                    choices=[512, 768, 1024],
+                    label="token batch length",
+                    value=512,
+                )
+                length_penalty = gr.inputs.Slider(
+                    minimum=0.5, maximum=1.0, label="length penalty", default=0.7, step=0.05
+                )
+            with gr.Row():
+                repetition_penalty = gr.inputs.Slider(
+                    minimum=1.0,
+                    maximum=5.0,
+                    label="repetition penalty",
+                    default=3.5,
+                    step=0.1,
+                )
+                no_repeat_ngram_size = gr.Radio(
+                    choices=[2, 3, 4],
+                    label="no repeat ngram size",
+                    value=3,
+                )
+            with gr.Row():
+                example_name = gr.Dropdown(
+                    list(name_to_path.keys()),
+                    label="Choose an Example",
+                )
+                load_examples_button = gr.Button(
+                    "Load Example",
+                )
             input_text = gr.Textbox(
                 lines=6,
                 label="input text",
                 placeholder="Enter text to summarize, the text will be cleaned and truncated on Spaces. Narrative, academic (both papers and lecture transcription), and article text work well. May take a bit to generate depending on the input text :)",
             )
             gr.Markdown("Upload your own file:")
-            uploaded_file = gr.File(
-                label="Upload a text file",
-                file_count="single",
-                type="file",
-            )
-            load_file_button = gr.Button("Load Uploaded File")
+            with gr.Row():
+                uploaded_file = gr.File(
+                    label="Upload a text file",
+                    file_count="single",
+                    type="file",
+                )
+                load_file_button = gr.Button("Load Uploaded File")
 
             gr.Markdown("---")
 
@@ -221,7 +226,10 @@ if __name__ == "__main__":
             gr.Markdown(
                 "Summary generation should take approximately 1-2 minutes for most settings."
             )
-            summarize_button = gr.Button("Summarize!")
+            summarize_button = gr.Button(
+                                "Summarize!",
+                                variant="primary",
+                                )
 
             output_text = gr.HTML("<p><em>Output will appear below:</em></p>")
             gr.Markdown("### Summary Output")