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import gradio as gr |
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import torch |
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from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler |
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model_id = "stabilityai/stable-diffusion-2-1" |
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32) |
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config) |
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def diffusion(text,num_inference_steps,guidance_scale): |
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prompt = text |
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image = pipe(prompt,guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0] |
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return image |
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demo = gr.Interface( |
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diffusion, |
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[ |
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gr.Textbox( |
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label="prompt text", |
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lines=3, |
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), |
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gr.Slider(1, 100, value=50), |
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gr.Slider(1.0, 30.0, value=7.5), |
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], |
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"image", |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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image.save("astronaut_rides_horse.png") |
