chore: Update minor formatting for the description

app.py

@@ -11,9 +11,9 @@ iface = gr.Interface(
     examples_per_page=4,
     inputs=[
         gr.inputs.Textbox(label="Patent Information", 
-                          placeholder="US9820315B2 or https://patents.google.com/patent/US9820315B2 ...", 
+                          placeholder="US10125002B2 or https://patents.google.com/patent/US10125002B2 ...", 
                           lines=1,
-                          default="US9820315B2"),
+                          default="US10125002B2"),
         gr.inputs.CheckboxGroup(summarizer.summary_options, 
                                 default=summarizer.summary_options,
                                 label="Summaries to Generate"),
@@ -44,32 +44,24 @@ iface = gr.Interface(
     description="""
     v.1.0.0
 
-    Reading through patent documents is oftentimes a long and tedious task. 
-    There are cases wherein one has to manually go through several pages 
-    in order to determine if the patent is relevant to the prior art search.
+    Reading through patent documents is oftentimes a long and tedious task. There are cases wherein one has to manually go through several pages in order to determine if the patent is relevant to the prior art search.
     
-    This application is meant to automate the initial phase of going through 
-    patents so that the potential inventor or researcher may lessen the time 
-    spent trying to filter documents.
+    This application is meant to automate the initial phase of going through patents so that the potential inventor or researcher may lessen the time spent trying to filter documents.
     
     The Patent Summarizer:
     ✏️ Provides an interface for user input
-    📂 Retrieves and parses the document based on the given patent information
+    📂 Retrieves and parses the document from Patents Google based on the given patent information
     📑 Returns summaries for the abstract, background, and/or claims.
     
     Models explored:
-    - Big Bird: Transformers for Longer Sequences
-    https://arxiv.org/abs/2007.14062
-    https://huggingface.co/google/bigbird-pegasus-large-bigpatent
-    - T5
-    https://arxiv.org/pdf/1910.10683.pdf
-    https://huggingface.co/cnicu/t5-small-booksum
-    - BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension 
-    https://arxiv.org/abs/1910.13461
-    https://huggingface.co/sshleifer/distilbart-cnn-6-6
-    - PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
-    https://arxiv.org/abs/1912.08777
-    https://huggingface.co/google/pegasus-xsum
+    🤖 Big Bird: Transformers for Longer Sequences
+    https://arxiv.org/abs/2007.14062 , https://huggingface.co/google/bigbird-pegasus-large-bigpatent
+    🤖 T5
+    https://arxiv.org/pdf/1910.10683.pdf , https://huggingface.co/cnicu/t5-small-booksum
+    🤖 BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension 
+    https://arxiv.org/abs/1910.13461, https://huggingface.co/sshleifer/distilbart-cnn-6-6
+    🤖 PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
+    https://arxiv.org/abs/1912.08777 , https://huggingface.co/google/pegasus-xsum
     """
 )