Update app.py

app.py

@@ -135,7 +135,7 @@ def load_and_prepare_model(model_id):
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++")
     #pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
     #pipe.scheduler = DPMSolverMultistepScheduler.from_pretrained('SG161222/RealVisXL_V5.0', subfolder='scheduler', algorithm_type='sde-dpmsolver++')
-    pipe.vae = vaeX.to(torch.bfloat16)
+    pipe.vae = vaeXL #.to(torch.bfloat16)
     #pipe.unet = unetX.to(torch.bfloat16)
     pipe.scheduler = sched
     pipe.vae.do_resize=False
@@ -240,7 +240,7 @@ def generate_30(
     randomize_seed: bool = False,
     use_resolution_binning: bool = True, 
     num_images: int = 1,  
-    juggernaut: bool = True,
+    juggernaut: bool = False,
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
@@ -249,8 +249,8 @@ def generate_30(
     gc.collect()
     global models
     pipe = models[model_choice]
-    if juggernaut == False:
-        pipe.vae=vaeXL
+    if juggernaut == True:
+        pipe.vae=vaeX
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
@@ -302,7 +302,7 @@ def generate_60(
     randomize_seed: bool = False,
     use_resolution_binning: bool = True, 
     num_images: int = 1,  
-    juggernaut: bool = True,
+    juggernaut: bool = False,
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
@@ -311,8 +311,8 @@ def generate_60(
     gc.collect()
     global models
     pipe = models[model_choice]
-    if juggernaut == False:
-        pipe.vae=vaeXL
+    if juggernaut == True:
+        pipe.vae=vaeX
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
@@ -364,7 +364,7 @@ def generate_90(
     randomize_seed: bool = False,
     use_resolution_binning: bool = True, 
     num_images: int = 1,  
-    juggernaut: bool = True,
+    juggernaut: bool = False,
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
@@ -373,8 +373,8 @@ def generate_90(
     gc.collect()
     global models
     pipe = models[model_choice]
-    if juggernaut == False:
-        pipe.vae=vaeXL
+    if juggernaut == True:
+        pipe.vae=vaeX
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
@@ -502,7 +502,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             value=0.3,
         )
         randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-        juggernaut = gr.Checkbox(label="Use Juggernaut VAE", value=True)
+        juggernaut = gr.Checkbox(label="Use Juggernaut VAE", value=False)
         with gr.Row():
             width = gr.Slider(
                 label="Width",