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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update modeling_modnet.py
Browse files- modeling_modnet.py +1 -1
modeling_modnet.py
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@@ -3,7 +3,7 @@ from torch import nn
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from transformers import PreTrainedModel, PretrainedConfig
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from .configuration_modnet import MODNetConfig
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from .modnet import MODNet
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class HF_MODNet(PreTrainedModel):
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from transformers import PreTrainedModel, PretrainedConfig
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from .configuration_modnet import MODNetConfig
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from .MODNet.modnet.modnet import MODNet
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class HF_MODNet(PreTrainedModel):
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