Video Classification
Transformers
PyTorch
Safetensors
English
xclip
feature-extraction
vision
Eval Results (legacy)
Instructions to use microsoft/xclip-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/xclip-large-patch14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="microsoft/xclip-large-patch14")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/xclip-large-patch14") model = AutoModel.from_pretrained("microsoft/xclip-large-patch14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b9b5ccd5981e68ada2f3ede7aff979286fb7dfc25a30f89b4ae4e87eeda9075
- Size of remote file:
- 2.3 GB
- SHA256:
- 452ba339d9f0213e0ef802af05f60742db1b73f95ee4aaf7ed5ca1108ae3ea46
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