Update app.py

app.py

@@ -113,7 +113,7 @@ def summarize_ner(text): # I implemented the validation step here because the mo
 demo = gr.Interface(fn=summarize_ner,
                     inputs=[gr.Textbox(label="Text to Summarize and find entities",
                                         lines=10,
-                                        placeholder= "Enter or Paste Text here"
+                                        placeholder= "Click the example below to see it in action or paste your text."
                                         )],
                     outputs=[gr.HighlightedText(label="Text with entities",
                                                 show_legend=True,
@@ -126,8 +126,7 @@ demo = gr.Interface(fn=summarize_ner,
                     <a href="https://banjiola.github.io/Olabanji-Olaniyan/" 
                     target="_blank">Olabaji Olaniyan</a>
                     <p>This tool helps you generate quick summaries from long-form text and highlights named entities such as <mark>people</mark>, <mark>organisations</mark>, and <mark>locations</mark>. The following models were used: the <code>bart-large-cnn</code> model for text summarisation and the <code>dslim/bert-base-NER</code> model for named entity recognition.This web application is an implementation of Text Summarization and Named Entity Recognition.</p></div>
-                    
-                     <p><b><i>Click the example below to see it in action or paste your text.</b></i></p>
+
                     """,
                     flagging_mode="never",
                     examples= [example_1, example_2],