| import gradio as gr | |
| from diffusers import DiffusionPipeline | |
| import torch | |
| pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16") | |
| pipe.enable_model_cpu_offload() | |
| 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() |