inference.py

import os
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline, DDIMScheduler

model_path = os.getenv('WEIGHTS_DIR')

scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False)
pipe = StableDiffusionPipeline.from_pretrained(model_path, scheduler=scheduler, safety_checker=None, torch_dtype=torch.float16).to("cuda")

g_cuda = None