Instructions to use nateraw/videomae-base-finetuned-ucf101-subset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/videomae-base-finetuned-ucf101-subset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="nateraw/videomae-base-finetuned-ucf101-subset")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("nateraw/videomae-base-finetuned-ucf101-subset") model = AutoModelForVideoClassification.from_pretrained("nateraw/videomae-base-finetuned-ucf101-subset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nateraw/videomae-base-finetuned-ucf101-subset: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/nateraw/videomae-base-finetuned-ucf101-subset/resolve/a54e68e62d69fc2c69ff3085f0f80d73648e233a/training_args.bin
- Command line
-
hf download hf://nateraw/videomae-base-finetuned-ucf101-subset@a54e68e62d69fc2c69ff3085f0f80d73648e233a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nateraw/videomae-base-finetuned-ucf101-subset/resolve/a54e68e62d69fc2c69ff3085f0f80d73648e233a/training_args.bin
3.44 kB
- Xet hash:
- 1e918db66bf69c9a26cb21c7ca78321df72c9f9f973390971ab5c8ef42fa508a
- Size of remote file:
- 3.44 kB
- SHA256:
- 6e8e88fdd7a6aae41a84003164250c537d65222c44615e794e61297a05f6c5b1
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