Instructions to use kabachuha/modelscope-damo-text2video-pruned-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use kabachuha/modelscope-damo-text2video-pruned-weights with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:kabachuha/modelscope-damo-text2video-pruned-weights') tokenizer = open_clip.get_tokenizer('hf-hub:kabachuha/modelscope-damo-text2video-pruned-weights') - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aed4a235a855a5cd523496db33c1557cc14764391cecc314d2f49b61c289add7
- Size of remote file:
- 2.61 GB
- SHA256:
- 930e9865584beae2405d29bc06a05db3bb6a5b34eedd40a7db29b9156ed7d098
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