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 AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/xclip-large-patch14") model = AutoModel.from_pretrained("microsoft/xclip-large-patch14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5562597e110b413d06210aad5f2cefd46d4b88ea544d1ebba2af2496c99cdf5d
- Size of remote file:
- 2.3 GB
- SHA256:
- 5dfd16f191d773419419419b3ed4f4b72c20923347b0265373bd733fd69f7332
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