---
license: apache-2.0
base_model:
- Qwen/Qwen2.5-7B-Instruct
pipeline_tag: text-generation
language:
- en
- zh
---
# Insight-V-Summary

## Model Summary

The Insight-V models are 7B parameter models based on Qwen2.5 language model with a context window of 32K tokens.

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.

- **Repository:** https://github.com/dongyh20/Insight-V
- **Languages:** English, Chinese
- **Paper:** https://arxiv.org/abs/2411.14432


### Model Architecture

- **Architecture:** Pre-trained [Oryx-ViT](https://huggingface.co/THUdyh/Oryx-ViT) + Qwen2.5-7B
- **Data:** a mixture of 1.2M image-text data
- **Precision:** BFloat16

#### Hardware & Software

- **Hardware:** 64 * NVIDIA Tesla A100
- **Orchestration:** HuggingFace Trainer
- **Code:** Pytorch

## Citation