Feature Extraction
OpenCLIP
English
clip
open-clip
vision-language
image-text-retrieval
cross-modal-retrieval
long-context
hyperbolic-learning
hyperbolic-geometry
lorentz-model
eccv-2026
Instructions to use jeeit17/HyFL-CLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use jeeit17/HyFL-CLIP with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:jeeit17/HyFL-CLIP') tokenizer = open_clip.get_tokenizer('hf-hub:jeeit17/HyFL-CLIP') - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f3df2fb591bdf43e8f74c7a3aeadf459bd910258f9e95951ea145547aee452e
- Size of remote file:
- 599 MB
- SHA256:
- 574648ab54ca0a0629720283c00d8880979b11f450ddea57254487cc3ab00f95
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.