Instructions to use kabachuha/potat1-with-text-encoder-original-format with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use kabachuha/potat1-with-text-encoder-original-format with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:kabachuha/potat1-with-text-encoder-original-format') tokenizer = open_clip.get_tokenizer('hf-hub:kabachuha/potat1-with-text-encoder-original-format') - Notebooks
- Google Colab
- Kaggle
Download text2video_pytorch_model.pth from kabachuha/potat1-with-text-encoder-original-format: direct link, hf CLI and curl.
- Browser
- Download file 2.82 GB
-
https://huggingface.co/kabachuha/potat1-with-text-encoder-original-format/resolve/main/text2video_pytorch_model.pth
- Command line
-
hf download hf://kabachuha/potat1-with-text-encoder-original-format/text2video_pytorch_model.pth
-
curl -L -o text2video_pytorch_model.pth https://huggingface.co/kabachuha/potat1-with-text-encoder-original-format/resolve/main/text2video_pytorch_model.pth
2.82 GB
- Xet hash:
- 9e7199d7600f05edf68cd97393fc139c4c8069d930956a0e4c4bd9742f8ec2f8
- Size of remote file:
- 2.82 GB
- SHA256:
- 2c9c35d05d9fa3b205dd3062b9412a5faadd5298893c70b392e97cb9e9ddf6d0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.