updated html

app.py

@@ -72,12 +72,12 @@ with gr.Blocks() as demo:
     # 5. --- Add your custom HTML section below ---
     gr.HTML("""
         <div style='border: 1px solid #eee; padding: 15px; margin-top: 20px; border-radius: 5px;'>
-            <h4 style='color: #555;'>About This Demo</h4>
-            <p>Description: This model is part of the extensive OPUS-MT project developed by the Language Technology Research Group at the University of Helsinki (Helsinki-NLP). It is specifically trained for machine translation from English to French. These models are based on the Transformer architecture and utilize SentencePiece for tokenization, making them efficient and effective for translation tasks across numerous language pairs</p>
-            <p>Architecture: The model employs a standard Transformer encoder-decoder architecture, specifically the MarianMT implementation within the transformers library, which is highly optimized for neural machine translation.</p>
-            <p>Intended Uses & Scope: The sole purpose of this model is to translate text from English into French. It is one instance within the larger OPUS-MT collection, which provides pre-trained models for a vast number of language directions.</p>
-            <p>Popularity Context: The high download counts associated with Helsinki-NLP/opus-mt-en-fr and other OPUS-MT models reflect their widespread adoption for translation tasks. The Helsinki-NLP group's work is highly regarded, and their models are known for quality and comprehensive language coverage, making them a standard choice for many translation applications built using the Hugging Face ecosystem.</p>
-            <p>Functionality: A user enters English text. The application utilizes a transformers translation pipeline, pre-configured for English-to-French translation using the specified Helsinki-NLP model, to generate the French equivalent, which is then displayed.</p>
+            <h2 style='color: #555;'>About This Demo</h2>
+            <p><b>Description:</b> This model is part of the extensive OPUS-MT project developed by the Language Technology Research Group at the University of Helsinki (Helsinki-NLP). It is specifically trained for machine translation from English to French. These models are based on the Transformer architecture and utilize SentencePiece for tokenization, making them efficient and effective for translation tasks across numerous language pairs</p>
+            <p><b>Architecture:</b> The model employs a standard Transformer encoder-decoder architecture, specifically the MarianMT implementation within the transformers library, which is highly optimized for neural machine translation.</p>
+            <p><b>Intended Uses & Scope:</b> The sole purpose of this model is to translate text from English into French. It is one instance within the larger OPUS-MT collection, which provides pre-trained models for a vast number of language directions.</p>
+            <p><b>Popularity Context:</b> The high download counts associated with Helsinki-NLP/opus-mt-en-fr and other OPUS-MT models reflect their widespread adoption for translation tasks. The Helsinki-NLP group's work is highly regarded, and their models are known for quality and comprehensive language coverage, making them a standard choice for many translation applications built using the Hugging Face ecosystem.</p>
+            <p><b>Functionality:</b> A user enters English text. The application utilizes a transformers translation pipeline, pre-configured for English-to-French translation using the specified Helsinki-NLP model, to generate the French equivalent, which is then displayed.</p>
         </div>
     """)