deepseek-ai / deepseek-vl-7b-base

DeepSeek-VL: An open-source Vision-Language Model designed for real-world vision and language understanding applications

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Run time and cost

This model costs approximately $0.0073 to run on Replicate, or 136 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A40 (Large) GPU hardware. Predictions typically complete within 11 seconds. The predict time for this model varies significantly based on the inputs.

Readme

DeepSeek-VL-7b-base

Introduction

Introducing DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. DeepSeek-VL possesses general multimodal understanding capabilities, capable of processing logical diagrams, web pages, formula recognition, scientific literature, natural images, and embodied intelligence in complex scenarios.

DeepSeek-VL: Towards Real-World Vision-Language Understanding

Github Repository

Haoyu Lu, Wen Liu, Bo Zhang, Bingxuan Wang, Kai Dong, Bo Liu, Jingxiang Sun, Tongzheng Ren, Zhuoshu Li, Yaofeng Sun, Chengqi Deng, Hanwei Xu, Zhenda Xie, Chong Ruan (*Equal Contribution, Project Leader)

Model Summary

DeepSeek-VL-7b-base uses the SigLIP-L and SAM-B as the hybrid vision encoder supporting 1024 x 1024 image input and is constructed based on the DeepSeek-LLM-7b-base which is trained on an approximate corpus of 2T text tokens. The whole DeepSeek-VL-7b-base model is finally trained around 400B vision-language tokens.

License

This code repository is licensed under the MIT License. The use of DeepSeek-VL Base/Chat models is subject to DeepSeek Model License. DeepSeek-VL series (including Base and Chat) supports commercial use.

Citation

@misc{lu2024deepseekvl,
      title={DeepSeek-VL: Towards Real-World Vision-Language Understanding}, 
      author={Haoyu Lu and Wen Liu and Bo Zhang and Bingxuan Wang and Kai Dong and Bo Liu and Jingxiang Sun and Tongzheng Ren and Zhuoshu Li and Yaofeng Sun and Chengqi Deng and Hanwei Xu and Zhenda Xie and Chong Ruan},
      year={2024},
      eprint={2403.05525},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}

Contact

If you have any questions, please raise an issue or contact us at service@deepseek.com.