Video Classification
Transformers
PyTorch
English
xclip
feature-extraction
vision
Eval Results (legacy)
Instructions to use microsoft/xclip-large-patch14-kinetics-600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/xclip-large-patch14-kinetics-600 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="microsoft/xclip-large-patch14-kinetics-600")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/xclip-large-patch14-kinetics-600") model = AutoModel.from_pretrained("microsoft/xclip-large-patch14-kinetics-600") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a90a3e3cd986ebb6b461d0da3947d2e352f58c8c141a5f5919f8ced7230aaf3
- Size of remote file:
- 2.3 GB
- SHA256:
- 6e59b5589348200d189b7576bd1c46028c1e108f2a44a08ddb46f8a2b952a828
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