Update app.py

app.py

@@ -48,8 +48,26 @@ with gr.Blocks() as demo:
     """
     **Comparing Stable Diffusion Models**
 
-    See https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline
+    ***Motivation***
 
+    Much of the motivation of this project was to compare open-source text-to-image models (I'd like to expand this beyond open-source as well).
+    I've seen bloggers recently blog about how AI generated images are stereotypical. See https://medium.com/pitfall/there-aint-no-diversity-equity-and-inclusion-when-it-comes-to-ai-0716718b313f as an example.
+    There's some assumptions that all models have these biases, so I wanted to investigate this myself so I built this comparisson tool.
+
+    In the process of building this, I thought of the use case where a developer is developing there own model -- or maybe fine-tuning an existing one -- and wants to compare the output of said model against a published one. This tool can help too!
+
+    I see this space evolving in the future to include a comprehensive list of popular text-to-image model, saving the user from going into Hugging Face and liking models to see them in this app. (Anything but providing models by free text was my goal).
+    Hopefully you gain use of this space, or Fork it and improve it. I'd love to hear people's feedback!
+
+    ***How to use this app***
+
+    This app uses a [DiffusionPipeline](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline) to generate images.
+
+    In the dropdown you will see models that you have liked on HuggingFace. If you've liked models that aren't "text-to-image" based models, using those will fail as the app expects users to choose up to two text-to-image models.
+    You can navigate [here](https://huggingface.co/models?pipeline_tag=text-to-image&library=diffusers&sort=trending) to get models that will work with this app. Go to the model card and like it; then upon refreshing this app you will see this model in the dropdown.
+
+    
+    For faster inference, you may want to duplicate the space and upgrade to GPU in settings. When I upgraded this space to T4 Medium compute, generating two images with two models took a little more than a minute.
 
     """)
     gr.LoginButton()