MetaCLIP model applied to 2.5 billion data points of CommonCrawl (CC). It was introduced in the paper
Demystifying CLIP Data by Xu et al. and first released in
this repository.
Disclaimer: The team releasing MetaCLIP did not write a model card for this model so this model card has been written by the Hugging Face team.
The
Demystifying CLIP Data paper aims to reveal CLIP’s method around training data curation. OpenAI never open-sourced code regarding their data preparation pipeline.
You can use the raw model for linking images with text in a shared embedding space. This enables things like zero-shot image classification, text-based image retrieval, image-based text retrieval, etc.
We refer to the
docs. Just replace the names of the models on the hub.
1@misc{xu2023demystifying,
2 title={Demystifying CLIP Data},
3 author={Hu Xu and Saining Xie and Xiaoqing Ellen Tan and Po-Yao Huang and Russell Howes and Vasu Sharma and Shang-Wen Li and Gargi Ghosh and Luke Zettlemoyer and Christoph Feichtenhofer},
4 year={2023},
5 eprint={2309.16671},
6 archivePrefix={arXiv},
7 primaryClass={cs.CV}
8}
