Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from optimum.intel.openvino import OVStableDiffusionPipeline
+from diffusers.training_utils import set_seed
+
+quantized_pipe = OVStableDiffusionPipeline.from_pretrained("OpenVINO/Stable-Diffusion-Pokemon-en-quantized", compile=False)
+quantized_pipe.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1)
+quantized_pipe.compile()
+
+prompt = "cartoon bird"
+
+def generate(image):
+    output = pipe(prompt, num_inference_steps=50, output_type="pil")
+    return output.images[0]
+
+gr.Interface(
+    fn=generate,
+    inputs=gr.inputs.Textbox(placeholder="cartoon bird", 
+                             label="Prompt"
+                             "query",
+                             lines=1),
+    outputs=gr.outputs.Image(type="auto", label="Generated Image"),
+    title="Quantized stable diffusion",
+    description="",
+    theme="huggingface",
+).launch()