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README.md
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<img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/IPsQk8gTTMD-ipTye3WED.png" width="100%" /> <img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/IPsQk8gTTMD-ipTye3WED.png" width="100%" />
</div> </div>
## 核心特性 ### 核心特性
MoE 架构：卓越性能，低推理成本<br> MoE 架构：卓越性能，低推理成本<br>
LLM 主干网络已升级为 混合专家（Mixture-of-Experts, MoE） 架构。这使得 Ovis2.6 能够扩展至 总计 300 亿参数，从而捕获海量知识与细微差异。关键在于，其推理过程中仅激活约 30 亿参数，确保了较低的推理成本和高吞吐量。<br> LLM 主干网络已升级为 混合专家（Mixture-of-Experts, MoE） 架构。这使得 Ovis2.6 能够扩展至 总计 300 亿参数，从而捕获海量知识与细微差异。关键在于，其推理过程中仅激活约 30 亿参数，确保了较低的推理成本和高吞吐量。<br>
增强的长序列与高分辨率处理能力<br> 增强的长序列与高分辨率处理能力<br>
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```bash ```bash
python inference.py python inference.py
``` ```
##### 多图输入 多图输入
```bash ```bash
python inference-mul.py python inference-mul.py
``` ```
##### 视频输入 视频输入
```bash ```bash
python inference-mov.py python inference-mov.py
``` ```
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| Ovis2.6 | 30B | BW1000 | 2 | [Modelscope](https://www.modelscope.cn/models/AIDC-AI/Ovis2.6-30B-A3B) | | Ovis2.6 | 30B | BW1000 | 2 | [Modelscope](https://www.modelscope.cn/models/AIDC-AI/Ovis2.6-30B-A3B) |
## 源码仓库及问题反馈 ## 源码仓库及问题反馈
- https://developer.sourcefind.cn/codes/modelzoo/ovis2.6_transformers - https://developer.sourcefind.cn/codes/modelzoo/ovis2.6_pytorch
## 参考资料 ## 参考资料
- https://www.modelscope.cn/models/AIDC-AI/Ovis2 - https://www.modelscope.cn/models/AIDC-AI/Ovis2
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