Test multiple generations on small models

app.py

@@ -55,23 +55,23 @@ def run_xlnc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pa
     
     return image, seed
 
-@spaces.GPU(duration=10)
+@spaces.GPU(duration=15)
 def run_sc(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)
     
     generator = torch.Generator(device="cuda").manual_seed(seed)
-    image = pipe_sc(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_sc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25, num_images_per_prompt=4).images   
     
     return image, seed
 
-@spaces.GPU(duration=10)
+@spaces.GPU(duration=15)
 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)
     
     generator = torch.Generator(device="cuda").manual_seed(seed)
-    image = pipe_snc(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_snc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25, num_images_per_prompt=4).images
     
     return image, seed