Update app.py

app.py

@@ -256,7 +256,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
     if Model == "SDXL 1.0":
         torch.cuda.empty_cache()
         torch.cuda.max_memory_allocated(device=device)
-        sdxl = DiffusionPipeline.from_pretrained("stabilityai/stable-cascade", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+        sdxl = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
         sdxl.enable_xformers_memory_efficient_attention()
         sdxl = sdxl.to(device)   
         torch.cuda.empty_cache()
@@ -266,7 +266,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
             torch.cuda.empty_cache()
             image = sdxl(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images
             torch.cuda.empty_cache()
-            sdxl = DiffusionPipeline.from_pretrained("stabilityai/stable-cascade-prior", 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")
+            sdxl = 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")
             sdxl.enable_xformers_memory_efficient_attention()
             sdxl = sdxl.to(device)
             torch.cuda.empty_cache()