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FLUX.1-Kontext-dev-SDNQ-uint4-svd-r32
Disty0/FLUX.1-Kontext-dev-SDNQ-uint4-svd-r32
FLUX.1-Kontext-dev-SDNQ-uint4-svd-r32 is a image-to-image model from Disty0. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as other.
4 bit (UINT4 with SVD rank 32) quantization of black-forest-labs/FLUX.1-Kontext-dev using SDNQ.
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From the Hugging Face model README
4 bit (UINT4 with SVD rank 32) quantization of black-forest-labs/FLUX.1-Kontext-dev using SDNQ.
Usage:
pip install git+https://github.com/Disty0/sdnq
import torch
import diffusers
from diffusers.utils import load_image
from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers
pipe = diffusers.FluxKontextPipeline.from_pretrained("Disty0/FLUX.1-Kontext-dev-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(
image=input_image,
prompt="Add a hat to the cat",
guidance_scale=2.5,
generator=torch.manual_seed(0),
).images[0]
image.save("flux-kontext-dev-sdnq-uint4-svd-r32.png.png")
Original BF16 vs SDNQ quantization comparison:
| Quantization | Model Size | Visualization |
|---|---|---|
| Input Image | - |  |
| Original BF16 | 23.8 GB |  |
| SDNQ UINT4 | 6.8 GB |  |
- Task
- Image-to-Image
- Library
- diffusers
- License
- other
- Created
- Oct 25, 2025
- Updated
- Oct 29, 2025