Create app.py

app.py

@@ -0,0 +1,17 @@
+import gradio as gr
+from diffusers import DiffusionPipeline
+
+def generate_image(steps):
+    pipeline = DiffusionPipeline.from_pretrained("nroggendorff/anime", use_safetensors=True)
+    pipe = pipeline#.to("cuda")
+    image = pipe(num_inference_steps=steps).images[0]
+    return image
+
+with gr.Blocks() as demo:
+    sampling_steps = gr.Slider(value=1000, minimum=20, maximum=1000, label="Sampling Steps", info="How many iterations per image")
+    btn = gr.Button("Generate Image")
+    output_image = gr.Image(label="Generated Image")
+    
+    btn.click(fn=generate_image, inputs=sampling_steps, outputs=output_image)
+
+demo.launch()