Update

app.py

@@ -14,7 +14,6 @@ DESCRIPTION = "# SDXL"
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1024"))
-ENABLE_REFINER = os.getenv("ENABLE_REFINER", "1") == "1"
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
@@ -26,14 +25,13 @@ pipe = DiffusionPipeline.from_pretrained(
     use_safetensors=True,
     variant="fp16",
 ).to(device)
-if ENABLE_REFINER:
-    refiner = DiffusionPipeline.from_pretrained(
-        "stabilityai/stable-diffusion-xl-refiner-1.0",
-        vae=vae,
-        torch_dtype=torch.float16,
-        use_safetensors=True,
-        variant="fp16",
-    ).to(device)
+refiner = DiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-refiner-1.0",
+    vae=vae,
+    torch_dtype=torch.float16,
+    use_safetensors=True,
+    variant="fp16",
+).to(device)
 
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
@@ -176,7 +174,7 @@ with gr.Blocks(css_paths="style.css") as demo:
                 step=32,
                 value=1024,
             )
-        apply_refiner = gr.Checkbox(label="Apply refiner", value=False, visible=ENABLE_REFINER)
+        apply_refiner = gr.Checkbox(label="Apply refiner", value=False)
         with gr.Row():
             guidance_scale_base = gr.Slider(
                 label="Guidance scale for base",