Create app.py

app.py

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+import gradio as gr
+from diffusers import AutoPipelineForText2Image
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+pipe.to(device)
+
+def infer(prompt):
+
+    prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
+    image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+
+    return image
+
+with gr.Blocks() as demo:
+    
+    with gr.Column():
+        
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
+            run_button = gr.Button("Run", scale=0)
+        
+        result = gr.Image(label="Result", show_label=False)
+
+    run_button.click(
+        fn = infer,
+        inputs = [prompt],
+        outputs = [result]
+    )
+
+demo.queue().launch()