Image Segmentation
Transformers
PyTorch
modnet
feature-extraction
image-matting
background-removal
computer-vision
custom-architecture
custom_code
Instructions to use boopathiraj/MODNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boopathiraj/MODNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="boopathiraj/MODNet", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("boopathiraj/MODNet", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download backbones/__pycache__/wrapper.cpython-312.pyc from boopathiraj/MODNet: direct link, hf CLI and curl.
- Browser
- Download file 4.46 kB
-
https://huggingface.co/boopathiraj/MODNet/resolve/main/backbones/__pycache__/wrapper.cpython-312.pyc
- Command line
-
hf download hf://boopathiraj/MODNet/backbones/__pycache__/wrapper.cpython-312.pyc
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curl -L -o wrapper.cpython-312.pyc https://huggingface.co/boopathiraj/MODNet/resolve/main/backbones/__pycache__/wrapper.cpython-312.pyc
4.46 kB
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