Update app.py

app.py

@@ -7,13 +7,13 @@ prior_pipeline = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-
 decoder_pipeline = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", variant="bf16", torch_dtype=torch.float16)
 
 @spaces.GPU
-def generate(prompt, negative_prompt, width, height, steps):
+def generate(prompt, negative_prompt, steps):
     prior_pipeline.enable_model_cpu_offload()
     prior_output = prior_pipeline(
         prompt=prompt,
         negative_prompt=negative_prompt,
-        width=width,
-        height=height,
+        width=1024,
+        height=1024,
         guidance_scale=4.0,
         num_images_per_prompt=1,
         num_inference_steps=steps
@@ -32,16 +32,14 @@ def generate(prompt, negative_prompt, width, height, steps):
 
 with gr.Blocks() as demo:
     with gr.Row():
-        prompt = gr.Textbox(label="Prompt")
+        prompt = gr.Textbox(label="Prompt", value="A perfectly red apple, 32K HDR, studio lighting")
         generate_btn = gr.Button("Generate")
 
     with gr.Row():
         output = gr.Image(label="Output")
 
     with gr.Accordion("Advanced", open=False):
-        negative_prompt = gr.Textbox(label="Negative Prompt")
-        width = gr.Slider(minimum=64, maximum=1024, value=512, step=2, label="Width")
-        height = gr.Slider(minimum=64, maximum=1024, value=512, step=2, label="Height")
+        negative_prompt = gr.Textbox(label="Negative Prompt", value="ugly")
         steps = gr.Slider(minimum=4, maximum=50, step=1, value=20, label="Steps")
 
     generate_btn.click(generate, inputs=[prompt, negative_prompt, width, height, steps], outputs=output)