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@@ -9,21 +9,21 @@ pipeline_tag: image-text-to-text
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  ## Introduction
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- Ovis is a novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings. For a comprehensive introduction, please refer to [Ovis paper](https://arxiv.org/abs/2405.20797) and [Ovis GitHub](https://github.com/AIDC-AI/Ovis).
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  <div align="center">
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/TIlymOb86R6_Mez3bpmcB.png" width="100%" />
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  </div>
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  ## Model
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- Built upon Ovis1.5, Ovis1.6 further enhances high-resolution image processing, is trained on a larger, more diverse, and higher-quality dataset, and refines the training process with DPO training following instruction-tuning.
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  | Ovis MLLMs | ViT | LLM | Model Weights |
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  |:------------------|:-----------:|:------------------:|:---------------------------------------------------------------:|
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  | Ovis1.6-Gemma2-9B | Siglip-400M | Gemma2-9B-It | [Huggingface](https://huggingface.co/AIDC-AI/Ovis1.6-Gemma2-9B) |
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  ## Performance
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- With just **10B** parameters, Ovis1.6-Gemma2-9B leads the [OpenCompass](https://github.com/open-compass/VLMEvalKit) benchmark among open-source MLLMs within **30B** parameters.
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  <div align="center">
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/FBw_icZic56Dm1XyzJaxA.png" width="100%" />
 
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  ---
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  ## Introduction
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+ **Ovis** is a novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings. For a comprehensive introduction, please refer to [Ovis paper](https://arxiv.org/abs/2405.20797) and [Ovis GitHub](https://github.com/AIDC-AI/Ovis).
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  <div align="center">
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/TIlymOb86R6_Mez3bpmcB.png" width="100%" />
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  </div>
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  ## Model
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+ Built upon Ovis1.5, **Ovis1.6** further enhances high-resolution image processing, is trained on a larger, more diverse, and higher-quality dataset, and refines the training process with DPO training following instruction-tuning.
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  | Ovis MLLMs | ViT | LLM | Model Weights |
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  |:------------------|:-----------:|:------------------:|:---------------------------------------------------------------:|
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  | Ovis1.6-Gemma2-9B | Siglip-400M | Gemma2-9B-It | [Huggingface](https://huggingface.co/AIDC-AI/Ovis1.6-Gemma2-9B) |
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  ## Performance
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+ With just **10B** parameters, **Ovis1.6-Gemma2-9B** leads the [OpenCompass](https://github.com/open-compass/VLMEvalKit) benchmark among open-source MLLMs within **30B** parameters.
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  <div align="center">
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  <img src="https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/FBw_icZic56Dm1XyzJaxA.png" width="100%" />