---
base_model: Qwen/Qwen2-VL-72B-Instruct
library_name: transformers
license: apache-2.0
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: TVC-72B
  results: []
pipeline_tag: image-text-to-text
---

## Model Summary

The TVC models are 72B parameter models based on Qwen2-VL-72B-Instruct model with a context window of 8K tokens.

- **Repository:** https://github.com/sun-hailong/TVC
- **Languages:** English, Chinese
- **Paper:** https://arxiv.org/abs/2503.13360

### Model Architecture

- **Architecture:** Qwen2-VL-72B-Instruct
- **Data:** a mixture of 300k long-chain reasoning data
- **Precision:** BFloat16

#### Hardware & Software

- **Hardware:** 64 * NVIDIA Tesla H20
- **Orchestration:** HuggingFace Trainer
- **Code:** Pytorch

### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3

## Citation
```
@article{sun2024mitigating,
    title={Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning},
    author={Sun, Hai-Long and Sun, Zhun and Peng, Houwen and Ye, Han-Jia},
    journal={arXiv preprint arXiv:2503.13360},
    year={2025}
}
```