Instructions to use jinmang2/mgfn-ucf101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinmang2/mgfn-ucf101 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import MGFNForVideoAnomalyDetection model = MGFNForVideoAnomalyDetection.from_pretrained("jinmang2/mgfn-ucf101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jinmang2/mgfn-ucf101: direct link, hf CLI and curl.
- Browser
- Download file 115 MB
-
https://huggingface.co/jinmang2/mgfn-ucf101/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jinmang2/mgfn-ucf101/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jinmang2/mgfn-ucf101/resolve/main/pytorch_model.bin
115 MB
- Xet hash:
- 3669f398feb14201f1ab324f408c3a5605b07973b463da05aac361e920790ddd
- Size of remote file:
- 115 MB
- SHA256:
- 34a2fd120f41ea9847ecccee12756aac5ee6df76548582d27c6a18bbc4c1a002
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