Zero-Shot Image Classification
OpenCLIP
Safetensors
datology
clip
vision
OpenCLIP
datacomp
image-text-retrieval
multimodal
Instructions to use DatologyAI/retr-opt-vit-b-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use DatologyAI/retr-opt-vit-b-32 with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:DatologyAI/retr-opt-vit-b-32') tokenizer = open_clip.get_tokenizer('hf-hub:DatologyAI/retr-opt-vit-b-32') - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DatologyAI/retr-opt-vit-b-32: direct link, hf CLI and curl.
- Browser
- Download file 3.64 MB
-
https://huggingface.co/DatologyAI/retr-opt-vit-b-32/resolve/main/tokenizer.json
- Command line
-
hf download hf://DatologyAI/retr-opt-vit-b-32/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DatologyAI/retr-opt-vit-b-32/resolve/main/tokenizer.json
3.64 MB
File too large to display, you can check the raw version instead.