metadata
license: other
license_name: flux-dev-non-commercial-license
license_link: LICENSE.md
base_model:
- black-forest-labs/FLUX.2-dev
base_model_relation: quantized
library_name: diffusers
tags:
- sdnq
- flux
- image-editing
- 4-bit
4 bit (UINT4 with SVD rank 32) quantization of black-forest-labs/FLUX.2-dev using SDNQ.
Usage:
pip install sdnq
import torch
import diffusers
from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers
from sdnq.common import use_torch_compile as triton_is_available
from sdnq.loader import apply_sdnq_options_to_model
pipe = diffusers.Flux2Pipeline.from_pretrained("Disty0/FLUX.2-dev-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)
# Enable INT8 MatMul for AMD, Intel ARC and Nvidia GPUs:
if triton_is_available and (torch.cuda.is_available() or torch.xpu.is_available()):
pipe.transformer = apply_sdnq_options_to_model(pipe.transformer, use_quantized_matmul=True)
pipe.text_encoder = apply_sdnq_options_to_model(pipe.text_encoder, use_quantized_matmul=True)
pipe.transformer = torch.compile(pipe.transformer) # optional for faster speeds
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")