Update app.py

app.py

@@ -52,7 +52,7 @@ YOUR_WORK_HTML = """
 """
 
 # ---- Hugging Face reference content ----
-HF_REFERENCE_HTML = """
+HF_REFERENCE_HTML = f"""
 <div id="hf-content" style="max-width: 800px; margin: auto; font-size: 16px; line-height: 1.6;">
     {IMAGE_HTML}
     <h1>Text Generation (Hugging Face Reference)</h1>
@@ -140,8 +140,7 @@ generator("Hello, I'm a language model,", max_length=30, num_return_sequences=3)
         Text-to-Text generation models have a separate pipeline called text2text-generation. 
         This pipeline takes an input containing the sentence including the task and returns the output of the accomplished task.
     <p>
-
-    <pre style="background: #f5f5f5; padding: 15px; border-radius: 5px; overflow-x: auto;">
+""" + """<pre style="background: #f5f5f5; padding: 15px; border-radius: 5px; overflow-x: auto;">
 from transformers import pipeline
 
 text2text_generator = pipeline("text2text-generation")