ColQwen is a model based on a novel model architecture and training strategy based on Vision Language Models (VLMs) to efficiently index documents from their visual features. It is a Qwen2.5-VL-3B extension that generates ColBERT- style multi-vector representations of text and images. It was introduced in the paper ColPali: Efficient Document Retrieval with Vision Language Models and first released in this repository

This version is the untrained base version to guarantee deterministic projection layer initialization.

If you use any datasets or models from this organization in your research, please cite the original dataset as follows:

Developed by: Metric AI Research Lab