| import gradio as gr | |
| import torch | |
| from diffusers import DiffusionPipeline | |
| def generate_image(prompt): | |
| model_id = "runwayml/stable-diffusion-v1-5" | |
| pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
| pipeline = pipeline.to("cuda") | |
| num_inference_steps = 20 | |
| generator = torch.Generator("cuda").manual_seed(0) | |
| image = pipeline(prompt, generator=generator, num_inference_steps=20).images[0] | |
| return image | |
| iface = gr.Interface( | |
| fn=generate_image, | |
| inputs="text", | |
| outputs="image", | |
| title="Diffusion d'images", | |
| description="Générez des images à partir d'une description.", | |
| ) | |
| iface.launch() |