---
tags:
- clip
library_name: open_clip
pipeline_tag: zero-shot-image-classification
license: cc-by-nc-4.0
datasets:
- visheratin/laion-coco-nllb
---

## Model Summary

NLLB-CLIP is a model that combines a text encoder from the [NLLB model](https://huggingface.co/facebook/nllb-200-distilled-600M) and an image encoder from the 
standard [CLIP](https://huggingface.co/openai/clip-vit-base-patch32). This allows us to extend the model capabilities 
to 201 languages of the Flores-200. NLLB-CLIP sets state-of-the-art on the [Crossmodal-3600](https://google.github.io/crossmodal-3600/) dataset by performing very 
well on low-resource languages. You can find more details about the model in the [paper](https://arxiv.org/abs/2309.01859).

## Acknowledgements

I thank [ML Collective](https://mlcollective.org/) for providing Google Cloud compute resources to train the OpenCLIP-compatible version of NLLB-CLIP.