Video Classification
Transformers
PyTorch
English
xclip
feature-extraction
vision
Eval Results (legacy)
Instructions to use microsoft/xclip-base-patch16-hmdb-16-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-16-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-16-shot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/xclip-base-patch16-hmdb-16-shot") model = AutoModel.from_pretrained("microsoft/xclip-base-patch16-hmdb-16-shot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/xclip-base-patch16-hmdb-16-shot: direct link, hf CLI and curl.
- Browser
- Download file 780 MB
-
https://huggingface.co/microsoft/xclip-base-patch16-hmdb-16-shot/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/xclip-base-patch16-hmdb-16-shot/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/xclip-base-patch16-hmdb-16-shot/resolve/main/pytorch_model.bin
780 MB
- Xet hash:
- a9ec05e2a34b7299f61097837568b13509de357d39fe6534a87415280c76fd51
- Size of remote file:
- 780 MB
- SHA256:
- deca00bfa44fc4e9351db4caf93fa9db521c3f4b44a40d2d63d81012292a149d
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