Update app.py

app.py

@@ -12,7 +12,8 @@ _INTRO = """
 # Identity Representation in Diffusion Models
 
 Explore the data generated from [DiffusionBiasExplorer](https://huggingface.co/spaces/society-ethics/DiffusionBiasExplorer)!
-This demo showcases patterns in the images generated from different prompts input to Stable Diffusion and Dalle-2 systems.
+This demo showcases patterns in images generated by Stable Diffusion and Dalle-2 systems.
+Specifically, images obtained from prompt inputs that span various gender- and ethnicity-related terms are clustered to show how those shape visual representations (more details below).
 We encourage users to take advantage of this app to explore those trends, for example through the lens of the following questions:
 - Find the cluster that has the most prompts denoting a gender or ethnicity that you identify with. Do you think the generated images look like you?
 - Find two clusters that have a similar distribution of gender terms but different distributions of ethnicity terms. Do you see any meaningful differences in how gender is visually represented?