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BiRefNet GGUF

BiRefNet is a model for dichotomous image segmentation (background removal). The weights in this repository are converted for lightweight inference on consumer hardware with vision.cpp.

Fuentehuggingface.co/Acly/BiRefNet-GGUF/tree/4f6018e2f35cedf26c8ddf0fec1475252f8ba280
TipoOtherModelo baseZhengPeng7/BiRefNetVersiónRevision 4f6018eBcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
84,5–420 MB
Modelo base
ZhengPeng7/BiRefNet
Versión
vRevision 4f6018e
Actualizado
20 oct 2026
Descargas
1,5 mil
Fuente
Hugging Face

Descripción de la fuente

GGUF models for BiRefNet

BiRefNet is a model for dichotomous image segmentation (background removal). The weights in this repository are converted for lightweight inference on consumer hardware with vision.cpp.

Run

Example inference with vision.cpp:

CLI

vision-cli birefnet -m BiRefNet-F16.gguf -i input.png -o mask.png --composite comp.png

C++

image_data image      = image_load("input.png");
backend_device device = backend_init();
birefnet_model model  = birefnet_load_model("BiRefNet-F16.gguf", device);
image_data mask       = birefnet_compute(model, image);
image_save(mask, "mask.png");

Fuentes

1 fuente
Hugging FacePrincipalVersión 4f6018e2f35cedf26c8ddf0fec1475252f8ba280
huggingface.co/Acly/BiRefNet-GGUF/tree/4f6018e2f35cedf26c8ddf0fec1475252f8ba280

Verificado 20 oct

Artefactos del modelo

3 artefactos

BiRefNet-dynamic-F16.gguf

gguf · 420 MB · SHA-256 c7add90033d5…dcf3 · Hugging Face

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BiRefNet-F16.gguf

gguf · 420 MB · SHA-256 5d5fd824c8fb…4d77 · Hugging Face

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BiRefNet-lite-F16.gguf

gguf · 84,5 MB · SHA-256 7b5397a2c98d…4fa5 · Hugging Face

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Extractos de fuentes

3 extractos
Readme3 agohuggingface.co/Acly/BiRefNet-GGUF

--- license: mit base_model: ZhengPeng7/BiRefNet tags: - background-removal - mask-generation - Dichotomous Image Segmentation - vision.cpp pipeline_tag: image-segmentation --- # GGUF models for BiRefNet BiRefNet is a model for dichotomous image segmentation (background removal). The weights in this repository are converted for lightweight inference on consumer hardware with [vision.cpp](https://github.com/Acly/vision.cpp). * Original repository: [ZhengPeng7/BiRefNet (Github)](https://github.com/ZhengPeng7/BiRefNet) * Original weights: [ZhengPeng7/BiRefNet (HuggingFace)](https://huggingface.co/ZhengPeng7/BiRefNet) ## Run Example inference with [vision.cpp](https://github.com/Acly/vision.cpp): #### CLI ```sh vision-cli birefnet -m BiRefNet-F16.gguf -i input.png -o mask.png --composite comp.png ``` #### C++ ```c++ image_data image = image_load("input.png"); backend_device device = backend_init(); birefnet_model model = birefnet_load_model("BiRefNet-F16.gguf", device); image_data mask = birefnet_compute(model, image); image_save(mask, "mask.png"); ```

Note20 octhuggingface.co/Acly/BiRefNet-GGUF

Source context: 1455 downloads · 17 likes · Pipeline image-segmentation · Repo Acly/BiRefNet-GGUF

Note3 agohuggingface.co/Acly/BiRefNet-GGUF

Source context: 1028 downloads · 15 likes · Pipeline image-segmentation · Repo Acly/BiRefNet-GGUF