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--- |
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license: apache-2.0 |
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base_model: |
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- Qwen/Qwen2.5-7B-Instruct |
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pipeline_tag: text-generation |
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language: |
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- en |
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- zh |
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--- |
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# Insight-V-Summary |
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## Model Summary |
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The Insight-V models are 7B parameter models based on Qwen2.5 language model with a context window of 32K tokens. |
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Insight-V offers **1)** a scalable data generation pipeline for long-chain, high-quality reasoning data, **2)** a multi-agent system that decomposes visual reasoning tasks into reasoning and summarization, and **3)** a two-stage training pipeline to enhance visual reasoning capabilities. Together, these contributions address key challenges in visual reasoning, providing a solid foundation for future research in MLLM reasoning. |
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- **Repository:** https://github.com/dongyh20/Insight-V |
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- **Languages:** English, Chinese |
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- **Paper:** https://arxiv.org/abs/2411.14432 |
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### Model Architecture |
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- **Architecture:** Pre-trained [Oryx-ViT](https://huggingface.co/THUdyh/Oryx-ViT) + Qwen2.5-7B |
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- **Data:** a mixture of 1.2M image-text data |
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- **Precision:** BFloat16 |
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#### Hardware & Software |
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- **Hardware:** 64 * NVIDIA Tesla A100 |
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- **Orchestration:** HuggingFace Trainer |
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- **Code:** Pytorch |
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## Citation |
