Disty0/FLUX.2-dev-SDNQ-uint4-svd-r32

4 bit (UINT4 with SVD rank 32) quantization of black-forest-labs/FLUX.2-dev using SDNQ.

Usage:

pip install git+https://github.com/Disty0/sdnq

import torch
import diffusers
from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers

pipe = diffusers.Flux2Pipeline.from_pretrained("Disty0/FLUX.2-dev-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()

prompt = "Realistic macro photograph of a hermit crab using a soda can as its shell, partially emerging from the can, captured with sharp detail and natural colors, on a sunlit beach with soft shadows and a shallow depth of field, with blurred ocean waves in the background. The can has the text `BFL Diffusers` on it and it has a color gradient that start with #FF5733 at the top and transitions to #33FF57 at the bottom."

image = pipe(
    prompt=prompt,
    generator=torch.manual_seed(42),
    num_inference_steps=50,
    guidance_scale=4,
).images[0]
image.save("flux-2-dev-sdnq-uint4-svd-r32.png")