Update app.py

app.py

@@ -79,33 +79,10 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
             image = sdxl(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 == 'FusionXL':
-        torch.cuda.empty_cache()
-        torch.cuda.max_memory_allocated(device=device)
-        pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1")
-        pipe.enable_xformers_memory_efficient_attention()
-        pipe = pipe.to(device)
-        torch.cuda.empty_cache()
-        if refine == "Yes":
-            torch.cuda.empty_cache()
-            torch.cuda.max_memory_allocated(device=device)
-            int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images
-            pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16") if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0")
-            pipe.enable_xformers_memory_efficient_attention()
-            pipe = pipe.to(device)
-            torch.cuda.empty_cache()
-            image = pipe(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
-            torch.cuda.empty_cache()
-            return image
-        else:
-            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
 
     return image
     
-gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Animagine XL 3.0', 'SDXL 1.0', 'FusionXL',], value='PhotoReal', label='Choose Model'),
+gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Animagine XL 3.0', 'SDXL 1.0',], value='PhotoReal', label='Choose Model'),
                                gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), 
                                gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
                                gr.Slider(512, 1024, 768, step=128, label='Height'),