quantization of "pixart sigma"

qunata.py

# https://huggingface.co/PixArt-alpha/PixArt-Sigma-XL-2-1024-MS/tree/main/transformer
# https://huggingface.co/blog/quanto-diffusers

#python -m venv quanta   or conda whatever
#source ./quanta/bin/activate >>> default (bash shell)


# pip install --force git+https://github.com/huggingface/diffusers.git
#  pip install  torch optimum.quanto
#run first part to create model 
#run second part to test model


####################firstpart#####################

# from diffusers import PixArtTransformer2DModel
# from optimum.quanto import QuantizedPixArtTransformer2DModel, qfloat8

# model = PixArtTransformer2DModel.from_pretrained("PixArt-alpha/PixArt-Sigma-XL-2-1024-MS", subfolder="transformer")
# qmodel = QuantizedPixArtTransformer2DModel.quantize(model, weights=qfloat8)
# qmodel.save_pretrained("pixart-sigma-fp8")

####################secondpart#####################

from optimum.quanto import QuantizedPixArtTransformer2DModel
import torch

transformer = QuantizedPixArtTransformer2DModel.from_pretrained("pixart-sigma-fp8") 
transformer.to(device="cuda", dtype=torch.float16)
from diffusers import DiffusionPipeline
import torch

pipe = DiffusionPipeline.from_pretrained(
    "PixArt-alpha/PixArt-Sigma-XL-2-1024-MS", 
    transformer=None,
    torch_dtype=torch.float16,
)

pipe.enable_sequential_cpu_offload()

pipe.transformer = transformer

prompt = "A small rose  with a happy face in the Sahara desert., master piece, award  wining "
image = pipe(prompt).images[0]

image.save("sd3_hello_world-8bit-T5.png")