Update app.py

app.py

@@ -164,7 +164,7 @@ if __name__ == "__main__":
         )
         with gr.Column():
 
-            gr.Markdown("## Load Text Inputs & Select Generation Parameters")
+            gr.Markdown("### Load Text Inputs & Select Model and Summary Type")
             gr.Markdown(
                 "Enter text below in the text area. The text will be summarized [using the selected text generation parameters](https://huggingface.co/blog/how-to-generate). Optionally load an available example below or upload a file."
             )
@@ -205,11 +205,11 @@ if __name__ == "__main__":
                     default=3.5,
                     step=0.1,
                 )
-                no_repeat_ngram_size = gr.Radio(
-                    choices=[2, 3, 4],
-                    label="no repeat ngram size",
-                    value=3,
-                )
+                #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()),
@@ -221,7 +221,7 @@ if __name__ == "__main__":
             input_text = gr.Textbox(
                 lines=6,
                 label="Input Text (for summarization)",
-                placeholder="Enter any scientific text to be condensed into a long and comprehensive digested format or an extreme TLDR summary version, the text will be preprocessed and truncated if necessary to fit within the computational constraints. The models were trained to handle long scientific papers but generalize reasonably well also to shorter text documents like abstracts with an appropriate. Might take a well to produce long summaries :)",
+                placeholder="Enter any scientific text to be condensed into a long and comprehensive digested format or an extreme TLDR summary version, the text will be preprocessed and truncated if necessary to fit within the computational constraints. The models were trained to handle long scientific papers but generalize reasonably well also to shorter text documents like abstracts with an appropriate. Might take a while to produce long summaries :)",
             )
             gr.Markdown("Upload your own file:")
             with gr.Row():