Update app.py

app.py

@@ -80,8 +80,7 @@ with gr.Blocks() as demo:
 
     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.
+    In the dropdown you will see models that you have liked on HuggingFace. Only models that you've likes and fit the criteria for this app will display in the dropdown. 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.