Update app.py

app.py

@@ -240,12 +240,12 @@ def to_base64(pil_image):
     return base64.b64encode(buffered.getvalue())
 
 title = "Interactive demo: glide-text2im dermoscopic image generator"
-description = "Demo for the Finetuned version of OpenAI's GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models."
+description = "Demo for the Finetuned version of OpenAI's GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. Please be aware that generation of the image will take up to 20 minutes, as CPU is used for the generation"
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2112.10741'>GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models</a> | <a href='https://github.com/openai/glide-text2im/'>Official Repo</a></p>"
-examples =["put in one of the following examples: melanoma; melanocytic nevi; Actinic keratoses and intraepithelial carcinoma / Bowen's disease; benign keratosis-like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratoses; basal cell carcinoma; dermatofibroma; vascular lesions | Please be aware that generation of the image will take up to 20 minutes, as CPU is used for the generation"]
+examples =["melanoma"]
 
 iface = gr.Interface(fn=sample, 
-                     inputs=gr.inputs.Textbox(label='What would you like to see?'), 
+                     inputs=gr.inputs.Textbox(label='Which dermoscopic entity would you like to see? Choose one of the following one: "melanoma", "melanocytic nevi", "Actinic keratoses and intraepithelial carcinoma / Bowen's disease; benign keratosis-like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratoses", "basal cell carcinoma", "dermatofibroma", "vascular lesions"'), 
                      outputs=gr.outputs.Image(type="pil", label="Model input + completions"),
                      title=title,
                      description=description,