mit-han-lab/svdquant-datasets
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How to use nunchaku-ai/nunchaku-flux.1-krea-dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("nunchaku-ai/nunchaku-flux.1-krea-dev", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
This repository contains Nunchaku-quantized versions of FLUX.1-Krea-dev, designed to generate high-quality images from text prompts. It is optimized for efficient inference while maintaining minimal loss in performance.
svdq-int4_r32-flux.1-krea-dev.safetensors: SVDQuant quantized INT4 FLUX.1-Krea-dev model. For users with non-Blackwell GPUs (pre-50-series).svdq-fp4_r32-flux.1-krea-dev.safetensors: SVDQuant quantized NVFP4 FLUX.1-Krea-dev model. For users with Blackwell GPUs (50-series).@inproceedings{
li2024svdquant,
title={SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models},
author={Li*, Muyang and Lin*, Yujun and Zhang*, Zhekai and Cai, Tianle and Li, Xiuyu and Guo, Junxian and Xie, Enze and Meng, Chenlin and Zhu, Jun-Yan and Han, Song},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025}
}
The FLUX.1 [dev] Model is licensed by Black Forest Labs Inc. under the FLUX.1 [dev] Non-Commercial License. Copyright Black Forest Labs Inc. IN NO EVENT SHALL BLACK FOREST LABS INC. BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.
Base model
black-forest-labs/FLUX.1-dev