Update app.py

app.py

@@ -15,8 +15,7 @@ with open('loras.json', 'r') as f:
     loras = json.load(f)
 
 # Initialize the base model
-base_model = "ariG23498/sd-3.5-merged"
-pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
+pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", torch_dtype=torch.bfloat16)
 
 MAX_SEED = 2**32-1
 
@@ -119,7 +118,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
     )
     	    # Info blob stating what the app is running
     info_blob = gr.HTML(
-        """<div id="info_blob"> SOON®'s curated LoRa Gallery & Art Manufactory Space.|Runs on Stable Diffusion 3.5 Turbo. Now testing HST-triggerable historic photo-trained LoRAs. </div>"""
+        """<div id="info_blob"> SOON®'s curated LoRa Gallery & Art Manufactory Space.|Runs on Stable Diffusion 3.5. Now testing HST-triggerable historic photo-trained LoRAs. </div>"""
     )
 
         # Info blob stating what the app is running
@@ -152,8 +151,8 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
         with gr.Accordion("Advanced Settings", open=True):
             with gr.Column():
                 with gr.Row():
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=.5, value=1.5)
-                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=8)
+                    cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=.5, value=4.5)
+                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=24)
                 
                 with gr.Row():
                     width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)