switch models

app.py

@@ -1,17 +1,14 @@
 import torch
 import spaces
-from diffusers import ControlNetUnionModel, AutoencoderKL, UNet2DConditionModel
+from diffusers import ControlNetUnionModel, AutoencoderKL
 import gradio as gr
 
 from pipeline.mod_controlnet_tile_sr_sdxl import StableDiffusionXLControlNetTileSRPipeline, calculate_overlap
 from pipeline.util import (
     SAMPLERS,    
-    create_hdr_effect,
-    optionally_disable_offloading,
-    progressive_upscale,
-    quantize_8bit,
-    select_scheduler,
-    torch_gc,    
+    create_hdr_effect,    
+    progressive_upscale,    
+    select_scheduler    
 )
 
 device = "cuda"
@@ -255,6 +252,7 @@ with gr.Blocks(css=css, theme=gr.themes.Ocean(), title="MoD ControlNet Tile Upsc
             )
             tile_gaussian_sigma = gr.Slider(label="Gaussian Sigma", minimum=0.05, maximum=1.0, step=0.01, value=0.3, visible=False)
             max_tile_size = gr.Dropdown(label="Max. Tile Size", choices=[1024, 1280], value=1024)
+        with gr.Row():
             resolution = gr.Slider(minimum=128, maximum=8192, value=2048, step=128, label="Resolution")
             num_inference_steps = gr.Slider(minimum=2, maximum=100, value=30, step=1, label="Inference Steps")
             guidance_scale = gr.Slider(minimum=1, maximum=20, value=6, step=0.1, label="Guidance Scale")
@@ -272,7 +270,7 @@ with gr.Blocks(css=css, theme=gr.themes.Ocean(), title="MoD ControlNet Tile Upsc
     with gr.Accordion(label="Example Images", open=True):
         with gr.Row(elem_id="examples_row"):
             with gr.Column(scale=12, elem_id="examples_container"):
-                eg = gr.Examples(
+                gr.Examples(
                     examples=[
                         [   "./examples/1.jpg",
                             "RealVisXL 5 Lightning",