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
- Xet hash:
- 1e5dc49453675e24d5e3994b9ac5e43e9002e0fe5c4de8429e2c6b0766c489d2
- Size of remote file:
- 1.97 GB
- SHA256:
- 24ca512c4d08a1487097ae60253c9800382a4264a8db7d84c7bf5b2bfac07800
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.