EntityNet
Collection
The models of our publication: Using Knowledge Graphs to harvest datasets for efficient CLIP model training • 7 items • Updated
How to use lmb-freiburg/CLIP-ViT-B-16-EntityNet-33M with OpenCLIP:
import open_clip
model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:lmb-freiburg/CLIP-ViT-B-16-EntityNet-33M')
tokenizer = open_clip.get_tokenizer('hf-hub:lmb-freiburg/CLIP-ViT-B-16-EntityNet-33M')A CLIP (Contrastive Language-Image Pre-training) model trained from scratch on EntityNet-33M.
See the project page for the paper, code, usage examples, metrics, etc.
The model has seen ~0.6B images at a batch size of 8k.