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MODEL Listed

Janus-Pro-7B

Janus-Pro-7B is a versatile 'any-to-any' multimodal model from the DeepSeek team, designed to bridge the gap between text and visual reasoning. Unlike traditional models that treat vision as a secondary input, Janus-Pro is built for seamless cross-modal generation and understanding. For developers, this means you can move beyond simple image captioning into complex tasks like high-fidelity image synthesis, visual document parsing, and sophisticated spatial reasoning within a single 7B parameter framework. Its architecture is optimized for efficiency, making it a strong candidate for edge deployment or integration into agentic workflows where both visual perception and creative output are required. While larger models offer brute-force reasoning, Janus-Pro provides a highly competitive performance-to-latency ratio, making it ideal for real-time applications like interactive UI assistants or automated visual content pipelines. It is released under the MIT license, ensuring high flexibility for commercial integration.

deepseek-aiany to any
01 / MODEL CARD

Model card

Janus-Pro-7B is a versatile 'any-to-any' multimodal model from the DeepSeek team, designed to bridge the gap between text and visual reasoning. Unlike traditional models that treat vision as a secondary input, Janus-Pro is built for seamless cross-modal generation and understanding. For developers, this means you can move beyond simple image captioning into complex tasks like high-fidelity image synthesis, visual document parsing, and sophisticated spatial reasoning within a single 7B parameter framework. Its architecture is optimized for efficiency, making it a strong candidate for edge deployment or integration into agentic workflows where both visual perception and creative output are required. While larger models offer brute-force reasoning, Janus-Pro provides a highly competitive performance-to-latency ratio, making it ideal for real-time applications like interactive UI assistants or automated visual content pipelines. It is released under the MIT license, ensuring high flexibility for commercial integration.

Model typeany to any
Providerdeepseek-ai
Licensemit
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/deepseek-ai/Janus-Pro-7B
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: deepseek-ai/Janus-Pro-7B
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model deepseek-ai/Janus-Pro-7B
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model deepseek-ai/Janus-Pro-7B README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('deepseek-ai/Janus-Pro-7B')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/deepseek-ai/Janus-Pro-7B.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/deepseek-ai/Janus-Pro-7B.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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