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  <img src="./figures/ant-bailing.png" width="100"/>
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  <p>
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- <p align="center">πŸ“‘ <a href="https://github.com/inclusionAI/Ming">Technical Report</a>ο½œπŸ“–<a href="https://lucaria-academy.github.io/Ming-Omni/">Project Page</a> ο½œπŸ€— <a href="https://huggingface.co/inclusionAI/Ming-Lite-Omni">Hugging Face</a>| πŸ€– <a href="https://www.modelscope.cn/models/inclusionAI/Ming-Lite-Omni">ModelScope</a>|
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  pip install diffusers==0.33.0
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  pip install nvidia-cublas-cu12==12.4.5.8 # for H20
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  ```
 
 
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  ```python
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  import os
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  This code repository is licensed under the [MIT License](../LICENSE), and the Legal Disclaimer is located in the [LEGAL.md file](../LEGAL.md) under the project's root directory.
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  <img src="./figures/ant-bailing.png" width="100"/>
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  <p>
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+ <p align="center">πŸ“‘ <a href="https://github.com/inclusionAI/Ming/blob/main/Ming_Omni.pdf">Technical Report</a>ο½œπŸ“–<a href="https://lucaria-academy.github.io/Ming-Omni/">Project Page</a> ο½œπŸ€— <a href="https://huggingface.co/inclusionAI/Ming-Lite-Omni">Hugging Face</a>| πŸ€– <a href="https://www.modelscope.cn/models/inclusionAI/Ming-Lite-Omni">ModelScope</a>
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  pip install diffusers==0.33.0
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  pip install nvidia-cublas-cu12==12.4.5.8 # for H20
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  ```
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+ Note: We test following examples on hardware of NVIDIA H800-80GB with CUDA 12.2. Loading inclusionAI/Ming-Lite-Omni in bfloat16 takes about 40890MB memory.
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  ```python
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  import os
 
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  This code repository is licensed under the [MIT License](../LICENSE), and the Legal Disclaimer is located in the [LEGAL.md file](../LEGAL.md) under the project's root directory.
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+ ## Citation
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+ If you find our work helpful, feel free to give us a cite.
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+ ```bibtex
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+ @article{Mingomni2025,
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+ title = {Ming-Omni: A Unified Multimodal Model for Perception and Generation},
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+ author = {Inclusion AI},
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+ journal = {arXiv preprint},
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+ year = {2025}
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+ }
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+ ```
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