Instructions to use UrNinja/VideoComposer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use UrNinja/VideoComposer with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:UrNinja/VideoComposer') tokenizer = open_clip.get_tokenizer('hf-hub:UrNinja/VideoComposer') - Notebooks
- Google Colab
- Kaggle
Download open_clip_pytorch_model.bin from UrNinja/VideoComposer: direct link, hf CLI and curl.
- Browser
- Download file 3.94 GB
-
https://huggingface.co/UrNinja/VideoComposer/resolve/main/open_clip_pytorch_model.bin
- Command line
-
hf download hf://UrNinja/VideoComposer/open_clip_pytorch_model.bin
-
curl -L -o open_clip_pytorch_model.bin https://huggingface.co/UrNinja/VideoComposer/resolve/main/open_clip_pytorch_model.bin
3.94 GB
- Xet hash:
- ca13b6933a993c9713cb1d541faa168cb1e93fea83c3368a1719b364515441ce
- Size of remote file:
- 3.94 GB
- SHA256:
- 9a78ef8e8c73fd0df621682e7a8e8eb36c6916cb3c16b291a082ecd52ab79cc4
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