Instructions to use google/vivit-b-16x2-kinetics400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vivit-b-16x2-kinetics400 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="google/vivit-b-16x2-kinetics400")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, ViViTForVideoClassification processor = AutoImageProcessor.from_pretrained("google/vivit-b-16x2-kinetics400") model = ViViTForVideoClassification.from_pretrained("google/vivit-b-16x2-kinetics400", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/vivit-b-16x2-kinetics400: direct link, hf CLI and curl.
- Browser
- Download file 356 MB
-
https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/vivit-b-16x2-kinetics400/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/pytorch_model.bin
356 MB
- Xet hash:
- 1a1ffbb51a326e71104474268b3fe42ddb81ba7bf436331d66d37d7bb76adb22
- Size of remote file:
- 356 MB
- SHA256:
- 160c79526e796d6101c4d9d0fe4000e26a6098a4d8e97f4cb8935fa6deb060d0
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