Image Segmentation
BiRefNet
Safetensors
Transformers
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 ezzdev/BiRefNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use ezzdev/BiRefNet with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("ezzdev/BiRefNet", 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("ezzdev/BiRefNet") - Transformers
How to use ezzdev/BiRefNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ezzdev/BiRefNet", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("ezzdev/BiRefNet", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eec2162eccfaab076d4f2d732a4fadf5f0b7ed97d49ec16ecc2c2f442a5752a8
- Size of remote file:
- 444 MB
- SHA256:
- 9ab37426bf4de0567af6b5d21b16151357149139362e6e8992021b8ce356a154
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