FlagEmbedding

[<img src="./imgs/FlagOpen.png">](https://flagopen.baai.ac.cn/)

<h1 align="center">⚡️BGE: One-Stop Retrieval Toolkit For Search and RAG</h1>

![bge_logo](./imgs/bge_logo.jpg)

<p align="center">
    <a href="https://huggingface.co/collections/BAAI/bge-66797a74476eb1f085c7446d">
        <img alt="Build" src="https://img.shields.io/badge/BGE_series-🤗-yellow">
    </a>
    <a href="https://github.com/FlagOpen/FlagEmbedding">
            <img alt="Build" src="https://img.shields.io/badge/Contribution-Welcome-blue">
    </a>
    <a href="https://github.com/FlagOpen/FlagEmbedding/blob/master/LICENSE">
        <img alt="License" src="https://img.shields.io/badge/LICENSE-MIT-green">
    </a>
    <a href="https://huggingface.co/C-MTEB">
        <img alt="Build" src="https://img.shields.io/badge/C_MTEB-🤗-yellow">
    </a>
    <a href="https://github.com/FlagOpen/FlagEmbedding/tree/master/research/baai_general_embedding">
        <img alt="Build" src="https://img.shields.io/badge/FlagEmbedding-1.3.0-red">
    </a>
</p>
<h4 align="center">
    <p>
        <a href=#news>News</a> |
        <a href=#installation>Installation</a> |
        <a href=#quick-start>Quick Start</a> |
        <a href=#community>Community</a> |
        <a href="https://github.com/FlagOpen/FlagEmbedding/tree/master/research">Projects</a> |
        <a href=#model-list>Model List</a> |
        <a href="#contributors">Contributor</a> |
        <a href="#citation">Citation</a> |
        <a href="#license">License</a> 
    <p>
</h4>


[English](README.md) | [中文](https://github.com/FlagOpen/FlagEmbedding/blob/master/README_zh.md)



## News

- 3/6/2025: :fire::fire: Introduce **BGE-VL** ([HF repo](https://huggingface.co/collections/BAAI/megapairs-67c6bbe49c15a9e7a7c69d92)), State-Of-The-Art multimodal embedding models to support Any visual search applications (everything, including text-to-image, image-to-text, image&prompt-to-image, text-to-image&text, and more)! They are released under the MIT license and are completely free for both academic and commercial use. We also release **MegaPairs** ([repo](https://github.com/VectorSpaceLab/MegaPairs), [paper](https://arxiv.org/abs/2412.14475)), a massive synthetic dataset which empowers BGE-VL!
- 12/5/2024: :book: We built the [BGE documentation](https://www.bge-model.com) for centralized BGE information and materials!
- 10/29/2024: :earth_asia: We created WeChat group for BGE. Scan the [QR code](./imgs/BGE_WeChat_Group.png) to join the group chat! To get the first hand message about our updates and new release, or having any questions or ideas, join us now!
- <img src="./imgs/BGE_WeChat_Group.png" alt="bge_wechat_group" class="center" width="200">

- 10/22/2024: We release another interesting model: [OmniGen](https://github.com/VectorSpaceLab/OmniGen), which is a unified image generation model supporting various tasks. OmniGen can accomplish complex image generation tasks without the need for additional plugins like ControlNet, IP-Adapter, or aux