change title

app.py

@@ -158,7 +158,7 @@ def generate_images_plots(prompt, model_name):
         genders.append(genderfromcaption(caption))
     return images, skintoneplot(skintones), genderplot(genders)
 
-with gr.Blocks(title="Skin Tone and Gender bias in Text to Image Models") as demo:
+with gr.Blocks(title="Skin Tone and Gender bias in Text-to-Image Generation Models") as demo:
     gr.Markdown("# Skin Tone and Gender bias in Text to Image Models")
     gr.Markdown('''
 In this demo, we explore the potential biases in text-to-image models by generating multiple images based on user prompts and analyzing the gender and skin tone of the generated subjects. Here's how the analysis works: