Create README.md

README.md

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+---
+base_model:
+- Qwen/Qwen2.5-VL-3B-Instruct
+language:
+- en
+library_name: colpali
+license: apache-2.0
+---
+# ColQwen2.5: Visual Retriever based on Qwen2.5-VL-3B-Instruct with ColBERT strategy
+
+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](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) extension that generates [ColBERT](https://arxiv.org/abs/2004.12832)- style multi-vector representations of text and images. 
+It was introduced in the paper [ColPali: Efficient Document Retrieval with Vision Language Models](https://arxiv.org/abs/2407.01449) and first released in [this repository](https://github.com/ManuelFay/colpali)
+
+This version is the untrained base version to guarantee deterministic projection layer initialization.
+
+
+## Usage
+
+> [!WARNING]
+> This version should not be used: it is solely the base version useful for deterministic LoRA initialization.
+
+
+## Citation
+
+If you use any datasets or models from this organization in your research, please cite the original dataset as follows:
+
+```bibtex
+@misc{faysse2024colpaliefficientdocumentretrieval,
+  title={ColPali: Efficient Document Retrieval with Vision Language Models}, 
+  author={Manuel Faysse and Hugues Sibille and Tony Wu and Bilel Omrani and Gautier Viaud and Céline Hudelot and Pierre Colombo},
+  year={2024},
+  eprint={2407.01449},
+  archivePrefix={arXiv},
+  primaryClass={cs.IR},
+  url={https://arxiv.org/abs/2407.01449}, 
+}
+```
+
+Developed by: Metric AI Research Lab