scaled linear + bh2

app.py

@@ -12,7 +12,7 @@ scheduler = UniPCMultistepScheduler(
     prediction_type="epsilon",
     predict_x0=True,
     thresholding=False,
-    solver_type='bh1',
+    solver_type='bh2',
     lower_order_final=True,
     disable_corrector=[0],
 )
@@ -64,7 +64,7 @@ else:
 
 device = "GPU 🔥" if torch.cuda.is_available() else "CPU 🥶"
 
-def inference(model_name, prompt, guidance, steps, width=512, height=512, seed=0, img=None, strength=0.5, neg_prompt=""):
+def inference(model_name, prompt, guidance, steps, width=512, height=512, seed=0, img=None, strength=0.5, neg_prompt="", order=2, solver_type="bh1"):
 
   global current_model
   for model in models:
@@ -257,7 +257,7 @@ with gr.Blocks(css=css) as demo:
 
     # model_name.change(lambda x: gr.update(visible = x == models[0].name), inputs=model_name, outputs=custom_model_group)
 
-    inputs = [model_name, prompt, guidance, steps, width, height, seed, image, strength, neg_prompt]
+    inputs = [model_name, prompt, guidance, steps, width, height, seed, image, strength, neg_prompt, order, solver_type]
     prompt.submit(inference, inputs=inputs, outputs=image_out)
 
     generate.click(inference, inputs=inputs, outputs=image_out)