Image Feature Extraction
OpenCLIP
PyTorch
English
fashion
image-retrieval
image-to-image
siglip
lookbench
embedding
vision-only
fp16
compressed
Instructions to use HopitAI/moda-fashion-vision-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use HopitAI/moda-fashion-vision-fp16 with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:HopitAI/moda-fashion-vision-fp16') tokenizer = open_clip.get_tokenizer('hf-hub:HopitAI/moda-fashion-vision-fp16') - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94bf21ec494bac0ff0d37c0c40490ac562a374f92ebd114699ff52744908e062
- Size of remote file:
- 186 MB
- SHA256:
- db0fea72d90c1ae37ddf8aeb086efdc6427741b5736aecdd473937713e7c38d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.