deepseek-vl2-tiny

About

What deepseek-vl2-tiny is

1. Introduction Introducing DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models that significantly improves upon its predecessor, DeepSeek-VL. DeepSeek-VL2 demonstrates superior capabilities across various tasks, including but not limited to visual question answering, optical character recognition, document/table/chart understanding, and visual grounding. Our model series is composed of three variants: DeepSeek-VL2-Tiny, DeepSeek-VL2-Small and DeepSeek-VL2, with 1.0B, 2.8B and 4.5B activated parameters respectively. DeepSeek-VL2 achieves competitive or state-of-the-art performance with similar or fewer activated parameters compared to existing open-source dense and MoE-based models. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding Github Repository Zhiyu Wu, Xiaokang Chen, Zizheng Pan, Xingchao Liu, Wen Liu, Damai Dai, Huazuo Gao, Yiyang Ma, Chengyue Wu, Bingxuan Wang, Zhenda Xie, Yu Wu, Kai Hu, Jiawei Wang, Yaofeng Sun, Yukun Li, Yishi Piao, Kang Guan, Aixin Liu, Xin Xie, Yuxiang You, Kai Dong, Xingkai Yu, Haowei Zhang, Liang Zhao, Yisong Wang, Chong Ruan ( Equal Contribution, Project Lead, Corresponding author) 2. Model Summary DeepSeek-VL2-tiny is built on DeepSeekMoE-3B (total activated parameters are 1.0B). 3. Quick Start Installation On the basis of Python = 3.8 environment, install the necessary dependencies by running the following command: Notifications 1. We suggest to use a temperature T <= 0.7 when sampling. We observe a larger temperature decreases the generation quality. 2. To keep the number of tokens managable in the context window, we apply dynamic tiling strategy to <=2 images. When there are =3 images, we directly pad the images to 384384 as inputs without tiling. 3. The main difference between DeepSeek-VL2-Tiny, DeepSeek-VL2-Small and DeepSeek-VL2 is the base LLM. Simple Inference Example Gradio Demo (TODO) 4. License This code repository is licensed under MIT License. The use of DeepSeek-VL2 models is subject to DeepSeek Model License. DeepSeek-VL2 series supports commercial use. 5. Citation 6. Contact If you have any questions, please raise an issue or contac

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys deepseek-vl2-tiny for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (deepseek-vl2-tiny below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-vl2-tiny","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Papers

Licence

Commercial licence needed

Sources

Weights & code

Explore

More language models