Update app.py

app.py

@@ -41,7 +41,7 @@ def run_xlc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag
         seed = random.randint(0, 9007199254740991)
     
     generator = torch.Generator(device="cuda").manual_seed(seed)
-    image = pipe_xlc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0]    
+    image = pipe_xlc(prompt, width=512, height=512, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0]    
     
     return image, seed
 
@@ -51,7 +51,7 @@ def run_xlnc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pa
         seed = random.randint(0, 9007199254740991)
     
     generator = torch.Generator(device="cuda").manual_seed(seed)
-    image = pipe_xlnc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0]    
+    image = pipe_xlnc(prompt, width=512, height=512, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0]    
     
     return image, seed
 
@@ -65,6 +65,7 @@ def run_sc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag_
     
     return image, seed
 
+@spaces.GPU
 def run_snc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag_layers=["mid"], randomize_seed=True, seed=42, progress=gr.Progress(track_tqdm=True)):
     if(randomize_seed):
         seed = random.randint(0, 9007199254740991)