Instructions to use muneeb1812/videomae-base-fake-video-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muneeb1812/videomae-base-fake-video-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="muneeb1812/videomae-base-fake-video-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("muneeb1812/videomae-base-fake-video-classification") model = AutoModelForVideoClassification.from_pretrained("muneeb1812/videomae-base-fake-video-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from muneeb1812/videomae-base-fake-video-classification: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/muneeb1812/videomae-base-fake-video-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://muneeb1812/videomae-base-fake-video-classification/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/muneeb1812/videomae-base-fake-video-classification/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- b1b0bf9183f6708cf4d6b54107c7de623486497bdab4e11d02c012b68f6fb4ce
- Size of remote file:
- 3.58 kB
- SHA256:
- 37f9df46d95ef3a30e0df3eb181486aa97a55127b443130f6822d44b34a954b2
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