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dataset_info:
features:
- name: text
dtype: string
- name: images
sequence: binary
splits:
- name: train
num_bytes: 39831925059
num_examples: 118193
download_size: 36493510192
dataset_size: 39831925059
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- visual-document-retrieval
license: cc-by-nc-4.0
library_name:
- transformers
tags:
- multimodal
- embeddings
- pretraining
- document-retrieval
- interleaved-data
---
# Copali train split used in MoCa Continual Pre-training
[🏠 Homepage](https://haon-chen.github.io/MoCa/) | [💻 Code](https://github.com/haon-chen/MoCa) | [🤖 MoCa-Qwen25VL-7B](https://huggingface.co/moca-embed/MoCa-Qwen25VL-7B) | [🤖 MoCa-Qwen25VL-3B](https://huggingface.co/moca-embed/MoCa-Qwen25VL-3B) | [📚 Datasets](https://huggingface.co/moca-embed/datasets) | [📄 Paper](https://arxiv.org/abs/2506.23115)
## Introduction
This is a interleaved multimodal pre-training dataset used in the modality-aware continual pre-training of MoCa models. It is adapted from [Copali](https://huggingface.co/datasets/Tevatron/colpali) and its [corpus](https://huggingface.co/datasets/Tevatron/colpali-corpus) by concatenating queries and positive documents.
The dataset consists of interleaved multimodal examples. text is a string containing text while images are image binaries that can be loaded with the following code snippet:
```python
import PIL.Image
from io import BytesIO
image_bytes = example['images'][0]
image = PIL.Image.open(BytesIO(image_bytes))
```
## Citation
MoCa
```bibtex
@article{chen2025moca,
title={MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings},
author={Chen, Haonan and Liu, Hong and Luo, Yuping and Wang, Liang and Yang, Nan and Wei, Furu and Dou, Zhicheng},
journal={arXiv preprint arXiv:2506.23115},
year={2025}
}
```
Colpali
```bibtex
@inproceedings{faysse2024colpali,
title={Colpali: Efficient document retrieval with vision language models},
author={Faysse, Manuel and Sibille, Hugues and Wu, Tony and Omrani, Bilel and Viaud, Gautier and Hudelot, C{\'e}line and Colombo, Pierre},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2024}
}
``` |