Instructions to use google/vivit-b-16x2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vivit-b-16x2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="google/vivit-b-16x2")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("google/vivit-b-16x2") model = AutoModelForVideoClassification.from_pretrained("google/vivit-b-16x2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:41df97234ff90175c5247a4842ae0d5dd2f1d1614ba66aa6e602f696d4463cac
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size 355839648
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