nunchaku-tech

--- base_model: Qwen/Qwen-Image-Edit-2509 base_model_relation: quantized datasets: - mit-han-lab/svdquant-datasets language: - en library_name: diffusers license: apache-2.0 pipeline_tag: text-to-image tags: - image-editing - SVDQuant - Qwen-Image-Edit-2509 - Diffusion - Quantization - ICLR2025

--- base_model: Qwen/Qwen-Image base_model_relation: quantized datasets: - mit-han-lab/svdquant-datasets language: - en library_name: diffusers license: apache-2.0 pipeline_tag: text-to-image tags: - text-to-image - SVDQuant - Qwen-Image - Diffusion - Quantization - ICLR2025

--- base_model: black-forest-labs/FLUX.1-Kontext-dev base_model_relation: quantized datasets: - mit-han-lab/svdquant-datasets language: - en library_name: diffusers license: other license_link: https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev/blob/main/LICENSE.md license_name: flux-1-dev-non-commercial-license pipeline_tag: image-to-image tags: - image-to-image - SVDQuant - FLUX.1-Kontext-dev - FLUX.1 - Diffusion - Quantization - ICLR2025

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. - Developed by: Nunchaku Team - Model type: text-to-image - License: flux-1-krea-dev-non-commercial-license - Quantized from model: FLUX.1-Krea-dev - `svdq-int4r32-flux.1-krea-dev.safetensors`: SVDQuant quantized INT4 FLUX.1-Krea-dev model. For users with non-Blackwell GPUs (pre-50-series). - `svdq-fp4r32-flux.1-krea-dev.safetensors`: SVDQuant quantized NVFP4 FLUX.1-Krea-dev model. For users with Blackwell GPUs (50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See flux.1-krea-dev.py. Just replace the safetensors with the ones from this repository. Check our tutorial for more advanced usage. - ComfyUI Usage: See nunchaku-flux.1-dev.json. Just replace the safetensors with the ones from this repository. 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.

This repository contains Nunchaku-quantized versions of FLUX.1-Fill-dev, capable of filling areas in existing images based on a text description. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team - Model type: image-to-image - License: flux-1-dev-non-commercial-license - Quantized from model: FLUX.1-Fill-dev - `svdq-int4r32-flux.1-fill-dev.safetensors`: SVDQuant quantized INT4 FLUX.1-Fill-dev model. For users with non-Blackwell GPUs (pre-50-series). - `svdq-fp4r32-flux.1-fill-dev.safetensors`: SVDQuant quantized NVFP4 FLUX.1-Fill-dev model. For users with Blackwell GPUs (50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See flux.1-fill-dev.py. Check our tutorial for more advanced usage. - ComfyUI Usage: See nunchaku-flux.1-fill-dev.json. 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.

This repository contains Nunchaku-quantized versions of FLUX.1-schnell, designed to generate high-quality images from text prompts. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team - Model type: text-to-image - License: apache-2.0 - Quantized from model: FLUX.1-schnell - `svdq-int4r32-flux.1-schnell.safetensors`: SVDQuant quantized INT4 FLUX.1-schnell model. For users with non-Blackwell GPUs (pre-50-series). - `svdq-fp4r32-flux.1-schnell.safetensors`: SVDQuant quantized NVFP4 FLUX.1-schnell model. For users with Blackwell GPUs (50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See flux.1-schnell.py. Check our tutorial for more advanced usage. - ComfyUI Usage: See nunchaku-flux.1-schnell.json.

This repository contains Nunchaku-quantized versions of FLUX.1-Depth-dev, capable of generating an image based on a text description while following the structure of a given input image. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team - Model type: image-to-image - License: flux-1-dev-non-commercial-license - Quantized from model: FLUX.1-Depth-dev - `svdq-int4r32-flux.1-depth-dev.safetensors`: SVDQuant quantized INT4 FLUX.1-Depth-dev model. For users with non-Blackwell GPUs (pre-50-series). - `svdq-fp4r32-flux.1-depth-dev.safetensors`: SVDQuant quantized NVFP4 FLUX.1-Depth-dev model. For users with Blackwell GPUs (50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See flux.1-depth-dev.py. Check our tutorial for more advanced usage. - ComfyUI Usage: See nunchaku-flux.1-depth-dev.json. 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.

This repository contains Nunchaku-quantized versions of stable-diffusion-xl-base-1.0, designed to generate high-quality images from text prompts. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team (thank @devgdovg) - Model type: text-to-image - License: openrail++ - Quantized from model: stable-diffusion-xl-base-1.0 - `svdq-int4r32-sdxl.safetensors`: SVDQuant quantized INT4 SDXL model. For users with non-Blackwell GPUs (pre-50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See sdxl.py or our tutorial for usage. - ComfyUI Usage: Stay tuned!

This repository contains Nunchaku-quantized versions of FLUX.1-Canny-dev, capable of generating an image based on a text description while following the structure of a given input image. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team - Model type: image-to-image - License: flux-1-dev-non-commercial-license - Quantized from model: FLUX.1-Canny-dev - `svdq-int4r32-flux.1-canny-dev.safetensors`: SVDQuant quantized INT4 FLUX.1-Canny-dev model. For users with non-Blackwell GPUs (pre-50-series). - `svdq-fp4r32-flux.1-canny-dev.safetensors`: SVDQuant quantized NVFP4 FLUX.1-Canny-dev model. For users with Blackwell GPUs (50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See flux.1-canny-dev.py. Check our tutorial for more advanced usage. - ComfyUI Usage: See nunchaku-flux.1-canny-dev.json. 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.

This repository contains Nunchaku-quantized versions of sdxl-turbo, designed to generate high-quality images from text prompts. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team (thank @devgdovg) - Model type: text-to-image - License: sai-nc-community - Quantized from model: sdxl-turbo - `svdq-int4r32-sdxl-turbo.safetensors`: SVDQuant quantized INT4 SDXL model. For users with non-Blackwell GPUs (pre-50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See sdxl-turbo.py or our tutorial for usage. - ComfyUI Usage: Stay tuned!

This repository contains Nunchaku-quantized versions of SANA-1.6B, designed to generate high-quality images from text prompts. It is optimized for efficient inference while maintaining minimal loss in performance. - Developed by: Nunchaku Team - Model type: text-to-image - License: NVIDIA License - Quantized from model: Sana1600M1024px - `svdq-int4r32-sana1.6b.safetensors`: SVDQuant quantized INT4 SANA-1.6B model. For users with non-Blackwell GPUs (pre-50-series). - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech

This repository contains Nunchaku-quantized versions of T5-XXL, used to encode text prompt to the embeddings. It is used to reduce the memory footprint of the model. - Developed by: Nunchaku Team - Model type: text-generation - License: apache-2.0 - Quantized from model: t5v11xxl - `awq-int4-flux.1-t5xxl.safetensors`: AWQ quantized W4A16 T5-XXL model for FLUX.1. - Inference Engine: nunchaku - Quantization Library: deepcompressor - Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models - Demo: demo.nunchaku.tech - Diffusers Usage: See flux.1-dev-qencoder.py. Check our tutorial for more advanced usage. - ComfyUI Usage: See nunchaku-flux.1-dev-qencoder.json.

handdrawngame.safetensors: Issue https://civitai.com/models/1118358?modelVersionId=1256866 relight-kontext-lora-single-captioncomfy.safetensors: Issue