Instructions to use mantelmoritz/CorridorKey-ONNX-Graphs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use mantelmoritz/CorridorKey-ONNX-Graphs with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 791 Bytes
082f53c | 1 2 3 4 5 6 7 8 9 10 11 12 | MODNet webcam portrait matting model, safetensors format
The model weights in model.safetensors are the official pre-trained MODNet webcam portrait matting
checkpoint (modnet_webcam_portrait_matting.ckpt) by Zhanghan Ke, Jiayu Sun, Kaican Li, Qiong Yan and
Rynson W.H. Lau, published at https://github.com/ZHKKKe/MODNet (commit
28165a451e4610c9d77cfdf925a94610bb2810fb). According to that repository's README, its code, models and demos
are released under the Apache License 2.0 (see LICENSE).
Modification: the checkpoint was converted from a PyTorch pickle to the safetensors format. All 751
state_dict entries keep their names and values. Tensors that the original checkpoint stores under two names
(module.backbone.* and module.lr_branch.backbone.*) are saved as two identical copies.
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