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)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("boopathiraj/MODNet", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- config.json +6 -6
config.json
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{
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"architectures": [
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"HF_MODNet"
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],
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"backbone": "mobilenetv2",
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"dtype": "float32",
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"model_type": "modnet",
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"
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{
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"model_type": "modnet",
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"backbone": "mobilenetv2",
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"architectures": ["HF_MODNet"],
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"auto_map": {
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"AutoConfig": "configuration_modnet.MODNetConfig",
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"AutoModel": "modeling_modnet.HF_MODNet"
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}
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}
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