Model reference · open weights
Janus is an open-weight language model from deepseek-ai. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | DeepSeek |
|---|---|
| Published under | deepseek-ai |
| Type | Language models |
| Task | Omni (any→any) |
| Parameters (lead) | 2.1B |
| Runs with | transformers |
| Released | 2024-10-18 |
| Popularity | 4k downloads / month |
| Licence | Open weights |
About
2024.10.20: We have uploaded the correct tokenizer_config.json. The previous file was missing the pad_token, which caused poor visual generation results.
Janus is a novel autoregressive framework that unifies multimodal understanding and generation. It addresses the limitations of previous approaches by decoupling visual encoding into separate pathways, while still utilizing a single, unified transformer architecture for processing. The decoupling not only alleviates the conflict between the visual encoder’s roles in understanding and generation, but also enhances the framework’s flexibility. Janus surpasses previous unified model and matches or exceeds the performance of task-specific models. The simplicity, high flexibility, and effectiveness of Janus make it a strong candidate for next-generation unified multimodal models.
Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation
Janus is a unified understanding and generation MLLM, which decouples visual encoding for multimodal understanding and generation. Janus is constructed based on the DeepSeek-LLM-1.3b-base which is trained on an approximate corpus of 500B text tokens. For multimodal understanding, it uses the SigLIP-L as the vision encoder, which supports 384 x 384 image input. For image generation, Janus uses the tokenizer from here with a downsample rate of 16.
Please refer to Github Repository
This code repository is licensed under the MIT License. The use of Janus models is subject to DeepSeek Model License.
@misc{wu2024janus,
title={Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation},
author={Chengyue Wu and Xiaokang Chen and Zhiyu Wu and Yiyang Ma and Xingchao Liu and Zizheng Pan and Wen Liu and Zhenda Xie and Xingkai Yu and Chong Ruan and Ping Luo},
year={2024},
eprint={2410.13848},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2410.13848},
}
If you have any questions, please raise an issue or contact us at service@deepseek.com.
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys janus for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (janus 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":"janus","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.