The mac m1 code calls huggingface Stable Diffusion (diffusers mode) Stable Diffusion xl

Stable Diffusion

from diffusers import DiffusionPipeline
import torch


pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
pipe = pipe.to("mps")

# Recommended if your computer has < 64 GB of RAM
pipe.enable_attention_slicing()


prompt = "便利店开业"
# First-time "warmup" pass if PyTorch version is 1.13 (see explanation above)
_ = pipe(prompt, num_inference_steps=1)

images = pipe(prompt=prompt).images[0]
images.save("output1.png")

diffusers

 The Hugging Face platform provides basic model weights and general model training framework diffusers

reference

How to use Stable Diffusion in Apple Silicon (M1/M2)

stable-diffusion-xl

from diffusers import StableDiffusionXLPipeline
import torch

# pipe = StableDiffusionXLPipeline.from_pretrained(
#     "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
# )
pipe = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0")

# pipe.to("cuda")
pipe = pipe.to("mps")
# Recommended if your computer has < 64 GB of RAM
pipe.enable_attention_slicing()

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
# First-time "warmup" pass if PyTorch version is 1.13 (see explanation above)
_ = pipe(prompt, num_inference_steps=1)
image = pipe(prompt=prompt).images[0]

image.save("sdxl.png")

https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/stable_diffusion_xl