Update app.py

app.py

@@ -349,25 +349,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
                torch.cuda.empty_cache()
                return image
-    if Model == 'CascadeXL':
-        torch.cuda.empty_cache()
-        from diffusers import StableCascadeCombinedPipeline
-        pipe = StableCascadeCombinedPipeline.from_pretrained("stabilityai/stable-cascade", torch_dtype=torch.float16)
-        pipe.enable_xformers_memory_efficient_attention()
-        pipe = pipe.to(device)
-        image = pipe(prompt=Prompt, negative_prompt=negative_prompt, num_inference_steps=10, prior_num_inference_steps=20, prior_guidance_scale=3.0, width=width, height=height).images[0]
-        
-        if upscale == 'Yes':
-            torch.cuda.empty_cache()
-            upscaler = DiffusionPipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, use_safetensors=True)
-            upscaler.enable_xformers_memory_efficient_attention()
-            upscaler = upscaler.to(device)
-            torch.cuda.empty_cache()
-            upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
-            return upscaled
-        else:
-            return image
-        
+    
     return image
     
 gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal', 'Animagine XL 3.0', 'SDXL 1.0', 'FusionXL', 'CascadeXL'], value='PhotoReal', label='Choose Model'),