Video Classification
Transformers
PyTorch
English
xclip
feature-extraction
vision
Eval Results (legacy)
Instructions to use microsoft/xclip-base-patch16-hmdb-2-shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/xclip-base-patch16-hmdb-2-shot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="microsoft/xclip-base-patch16-hmdb-2-shot")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/xclip-base-patch16-hmdb-2-shot") model = AutoModel.from_pretrained("microsoft/xclip-base-patch16-hmdb-2-shot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bec5c31ee6713dafe26f46ac5854e97749beebdb742ab35e8fc8235a92913b1
- Size of remote file:
- 780 MB
- SHA256:
- adec9b7c4e8cc1d176973d7f3fa22dbd616cd50345d7cd03058c84f2bb429717
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