| from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler | |
| import torch | |
| def dummy(images, **kwargs): | |
| return images, False | |
| async def Gimager(prompt): | |
| model_id = "SG161222/Realistic_Vision_V1.4" | |
| scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler") | |
| pipe = await StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16) | |
| pipe = pipe.to("cuda") | |
| pipe.safety_checker = dummy | |
| image = await pipe(prompt).images[0] | |
| return image | |