Update app.py

app.py

@@ -488,6 +488,18 @@ if __name__ == "__main__":
     logger.info("Starting app instance")
     with demo:
         with gr.Column():
+            gr.Markdown("# Document Summarization with Long-Document Transformers")
+            gr.Markdown(
+                """An example use case for fine-tuned long document transformers. Model(s) are trained on [book summaries](https://hf.co/datasets/kmfoda/booksum). Architectures [in this demo](https://hf.co/spaces/pszemraj/document-summarization) are [LongT5-base](https://hf.co/pszemraj/long-t5-tglobal-base-16384-book-summary) and [Pegasus-X-Large](https://hf.co/pszemraj/pegasus-x-large-book-summary).
+    
+                **Want more performance? Run this demo from a free Google Colab GPU:**.
+                <br>
+                <a href="https://colab.research.google.com/gist/pszemraj/52f67cf7326e780155812a6a1f9bb724/document-summarization-on-gpu.ipynb">
+                <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
+                </a>
+                <br>
+                """
+            )
             gr.Markdown("## Load Inputs & Select Parameters")
             gr.Markdown(
                 """Enter/paste text below, or upload a file. Pick a model & adjust params (_optional_), and press **Summarize!**
@@ -531,18 +543,6 @@ if __name__ == "__main__":
                     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("---")
-        gr.Markdown("# Document Summarization with Long-Document Transformers")
-        gr.Markdown(
-            """An example use case for fine-tuned long document transformers. Model(s) are trained on [book summaries](https://hf.co/datasets/kmfoda/booksum). Architectures [in this demo](https://hf.co/spaces/pszemraj/document-summarization) are [LongT5-base](https://hf.co/pszemraj/long-t5-tglobal-base-16384-book-summary) and [Pegasus-X-Large](https://hf.co/pszemraj/pegasus-x-large-book-summary).
-
-            **Want more performance? Run this demo from a free Google Colab GPU:**.
-            <br>
-            <a href="https://colab.research.google.com/gist/pszemraj/52f67cf7326e780155812a6a1f9bb724/document-summarization-on-gpu.ipynb">
-            <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
-            </a>
-            <br>
-            """
-        )
         with gr.Column():
             gr.Markdown("## Generate Summary")
             with gr.Row():