Image Segmentation
BiRefNet
Safetensors
background-removal
mask-generation
Dichotomous Image Segmentation
Camouflaged Object Detection
Salient Object Detection
pytorch_model_hub_mixin
model_hub_mixin
custom_code
Instructions to use wefttechnologies/BiRefNet2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use wefttechnologies/BiRefNet2 with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("wefttechnologies/BiRefNet2", trust_remote_code=True)# Option 2: use with BiRefNet # Install from https://github.com/ZhengPeng7/BiRefNet from models.birefnet import BiRefNet model = BiRefNet.from_pretrained("wefttechnologies/BiRefNet2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df012d574274c4e4a8f10c73ee269721a37b2ca41ecb117a073b30fd0a1af68a
- Size of remote file:
- 885 MB
- SHA256:
- 77277264c0e8c74149d3ff2fade4fd8176965b7108f3c5fc3b8c9c811edb4519
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.