deepseek vl 7b chat EU AI Act Compliance Profile

1. 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, Hao Yang, Yaofeng Sun, Chengqi Deng, Hanwei Xu, Zhenda Xie, Chong Ruan (*Equal Contribution, **Project Lead)

2. 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. DeekSeel-VL-7b-chat is an instructed version based on DeepSeek-VL-7b-base.

3. Quick Start

Installation

On the basis of Python >= 3.8 environment, install the necessary dependencies by running the following command:

git clone https://github.com/deepseek-ai/DeepSeek-VL
cd DeepSeek-VL

pip install -e .

Simple Inference Example

import torch
from transformers import AutoModelForCausalLM

from deepseek_vl.models import VLChatProcessor, MultiModalityCausalLM
from deepseek_vl.utils.io import load_pil_images


# specify the path to the model
model_path = "deepseek-ai/deepseek-vl-7b-chat"
vl_chat_processor: VL

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