Image Segmentation
ONNX
BiRefNet
Chinese
background-removal
matting
rembg
sam
u2net
clipseg
vitmatte
Instructions to use jkyy/yang-pixelcut-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use jkyy/yang-pixelcut-models with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("jkyy/yang-pixelcut-models", 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("jkyy/yang-pixelcut-models") - Notebooks
- Google Colab
- Kaggle
Download models/clipseg/tokenizer.json from jkyy/yang-pixelcut-models: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/jkyy/yang-pixelcut-models/resolve/main/models/clipseg/tokenizer.json
- Command line
-
hf download hf://jkyy/yang-pixelcut-models/models/clipseg/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/jkyy/yang-pixelcut-models/resolve/main/models/clipseg/tokenizer.json
2.22 MB
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