A CLIP (Contrastive Language-Image Pre-training) model trained on DFN-2B.
Data Filtering Networks (DFNs) are small networks used to automatically filter large pools of uncurated data.
This model was trained on 2B images that were filtered from a pool of 12.8B uncurated image-text pairs
(12.8B image-text pairs from CommonPool-12.8B).
This model has been converted to PyTorch from the original JAX checkpoints from Axlearn (
https://github.com/apple/axlearn
).
These weights are directly usable in OpenCLIP (image + text).
Model Details
Model Type:
Contrastive Image-Text, Zero-Shot Image Classification.
@article{fang2023data,
title={Data Filtering Networks},
author={Fang, Alex and Jose, Albin Madappally and Jain, Amit and Schmidt, Ludwig and Toshev, Alexander and Shankar, Vaishaal},
journal={arXiv preprint arXiv:2309.17425},
year={2023}
}
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