give up trying to format

app.py

@@ -101,14 +101,7 @@ if __name__ == "__main__":
     model, tokenizer = load_model_and_tokenizer("pszemraj/led-large-book-summary")
     model_sm, tokenizer_sm = load_model_and_tokenizer("pszemraj/led-base-book-summary")
     title = "Long-Form Summarization: LED & BookSum"
-    description = """A simple demo of how to use a fine-tuned LED model to summarize long-form text.
-
-    - [This model](https://huggingface.co/pszemraj/led-large-book-summary) is a fine-tuned version of [allenai/led-large-16384](https://huggingface.co/allenai/led-large-16384) on the [BookSum dataset](https://arxiv.org/abs/2105.08209).
-
-    - The goal was to create a model that can generalize well and is useful in summarizing lots of text in academic and daily usage.
-
-    - See [model card](https://huggingface.co/pszemraj/led-large-book-summary) for a notebook with GPU inference (much faster) on Colab.
-    """
+    description = "A simple demo of how to use a fine-tuned LED model to summarize long-form text. [This model](https://huggingface.co/pszemraj/led-large-book-summary) is a fine-tuned version of [allenai/led-large-16384](https://huggingface.co/allenai/led-large-16384) on the [BookSum dataset](https://arxiv.org/abs/2105.08209).The goal was to create a model that can generalize well and is useful in summarizing lots of text in academic and daily usage. See [model card](https://huggingface.co/pszemraj/led-large-book-summary) for a notebook with GPU inference (much faster) on Colab."
     gr.Interface(
         proc_submission,
         inputs=[