Update app.py

app.py

@@ -25,7 +25,7 @@ else:
     #refiner = refiner.to(device)
     #refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
 
-def genie (prompt, negative_prompt, height, width, scale, steps, seed, prompt_2, negative_prompt_2, high_noise_frac):
+def genie (prompt, height, width, steps, seed, prompt_2):
     generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
     int_image = pipe(prompt, prompt_2=prompt_2, height=height, width=width, num_inference_steps=steps, num_images_per_prompt=1, generator=generator, guidance_scale=0.0).images[0] 
     #image = refiner(prompt=prompt, prompt_2=prompt_2, negative_prompt=negative_prompt, negative_prompt_2=negative_prompt_2, image=int_image, denoising_start=high_noise_frac).images[0]   
@@ -35,12 +35,12 @@ gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generat
     gr.Textbox(label='What you Do Not want the AI to generate.'), 
     gr.Slider(512, 1024, 768, step=128, label='Height'),
     gr.Slider(512, 1024, 768, step=128, label='Width'),
-    gr.Slider(1, 15, 10, label='Guidance Scale'), 
+    #gr.Slider(1, 15, 10, label='Guidance Scale'), 
     gr.Slider(1, maximum=5, value=2, step=1, label='Number of Iterations'), 
     gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True),
     gr.Textbox(label='Embedded Prompt'),
-    gr.Textbox(label='Embedded Negative Prompt'),
-    gr.Slider(minimum=.7, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %')],
+    #gr.Textbox(label='Embedded Negative Prompt'),
+    #gr.Slider(minimum=.7, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %')],
     outputs='image', 
     title="Stable Diffusion XL 1.0 CPU or GPU", 
     description="SDXL 1.0 CPU or GPU. Currently running on CPU. <br><br><b>WARNING:</b> Extremely Slow. 65s/Iteration. Expect 25-50mins an image for 25-50 iterations respectively. This model is capable of producing NSFW (Softcore) images.",