Create app.py

app.py

@@ -0,0 +1,35 @@
+import torch
+import spaces
+import gradio as gr
+from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
+
+prior_pipeline = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=dtype)#.to("CUDA")
+#decoder_pipeline = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade",  torch_dtype=dtype)#.to("CUDA") 
+
+def generate(prompt, negative_prompt, width, height, steps):
+    prior_output = prior_pipeline(
+        prompt=prompt,
+        height=height,
+        width=width,
+        num_inference_steps=steps,
+        negative_prompt=negative_prompt
+    )
+    return prior_output
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        prompt = gr.Textbox(label="Prompt")
+
+    with gr.Row():
+        generate_btn = gr.Button("Generate")
+        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, step=64, label="Width")
+        height = gr.Slider(minimum=64, maximum=1024, step=64, label="Height")
+        steps = gr.Slider(minimum=1, maximum=50, step=1, label="Steps")
+
+    generate_btn.click(generate, inputs=[prompt, negative_prompt, width, height, steps], outputs=output)
+
+demo.launch()