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import torch
from PIL.Image import Image
from diffusers import StableDiffusionXLPipeline
from pipelines.models import TextToImageRequest
from torch import Generator
def load_pipeline() -> StableDiffusionXLPipeline:
pipeline = StableDiffusionXLPipeline.from_pretrained(
"./models/newdream-sdxl-20",
torch_dtype=torch.float16,
local_files_only=True,
).to("cuda")
pipeline(prompt="")
return pipeline
def infer(request: TextToImageRequest, pipeline: StableDiffusionXLPipeline) -> Image:
generator = Generator(pipeline.device).manual_seed(request.seed) if request.seed else None
return pipeline(
prompt=request.prompt,
negative_prompt=request.negative_prompt,
width=request.width,
height=request.height,
generator=generator,
).images[0]
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