Update app.py

app.py

@@ -41,4 +41,34 @@ with autocast("cuda"), torch.inference_mode():
     ).images
 
 for img in images:
-    display(img)
+    display(img)
+
+def inference(prompt, negative_prompt, num_samples, height=512, width=512, num_inference_steps=50, guidance_scale=7.5):
+    with torch.autocast("cuda"), torch.inference_mode():
+        return pipe(
+                prompt, height=int(height), width=int(width),
+                negative_prompt=negative_prompt,
+                num_images_per_prompt=int(num_samples),
+                num_inference_steps=int(num_inference_steps), guidance_scale=guidance_scale,
+                generator=g_cuda
+            ).images
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Prompt", value="photo of zwx dog in a bucket")
+            negative_prompt = gr.Textbox(label="Negative Prompt", value="")
+            run = gr.Button(value="Generate")
+            with gr.Row():
+                num_samples = gr.Number(label="Number of Samples", value=4)
+                guidance_scale = gr.Number(label="Guidance Scale", value=7.5)
+            with gr.Row():
+                height = gr.Number(label="Height", value=512)
+                width = gr.Number(label="Width", value=512)
+            num_inference_steps = gr.Slider(label="Steps", value=24)
+        with gr.Column():
+            gallery = gr.Gallery()
+
+    run.click(inference, inputs=[prompt, negative_prompt, num_samples, height, width, num_inference_steps, guidance_scale], outputs=gallery)
+
+demo.launch(debug=True)