sd_xl_turbo from_single_file 本地加载_diffusers from single file

from diffusers import EulerAncestralDiscreteScheduler
from diffusers import StableDiffusionXLPipeline
import torch
 
pipeline = StableDiffusionXLPipeline.from_single_file("sd_xl_turbo_1.0_fp16.safetensors",
                                                      torch_dtype=torch.float16, variant="fp16")
pipeline = pipeline.to("cuda")
 
prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
 
scheduler_dict = {
                "beta_end": 0.012,
                "beta_schedule": "scaled_linear",
                "beta_start": 0.00085,
                "clip_sample": False,
                "interpolation_type": "linear",
                "num_train_timesteps": 1000,
                "prediction_type": "epsilon",
                "sample_max_value": 1.0,
                "set_alpha_to_one": False,
                "skip_prk_steps": True,
                "steps_offset": 1,
                "timestep_spacing": "trailing",
                "trained_betas": None,
            }
pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config(scheduler_dict)
image = pipeline(prompt=prompt, guidance_scale=0.0, num_inference_steps=1, height=512, width=512).images[0]
image.save('test.png')