README.md

---
license: apache-2.0
datasets:
- remyxai/OpenSpaces
tags:
- remyx
base_model:
- Qwen/Qwen2.5-VL-3B-Instruct
---


# Model Card for SpaceQwen2.5-VL-3B-Instruct

**SpaceQwen2.5-VL-3B-Instruct** uses LoRA to fine-tune [Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) on a [dataset](https://huggingface.co/datasets/salma-remyx/OpenSpaces) designed with [VQASynth](https://github.com/remyxai/VQASynth/tree/main) to enhance spatial reasoning as in [SpatialVLM](https://spatial-vlm.github.io/)

## Model Details

### Model Description

This model uses data synthesis techniques and publically available models to reproduce the work described in SpatialVLM to enhance the spatial reasoning of multimodal models.
With a pipeline of expert models, we can infer spatial relationships between objects in a scene to create VQA dataset for spatial reasoning.


- **Developed by:** remyx.ai
- **Model type:** MultiModal Model, Vision Language Model, Qwen2.5-VL-3B-Instruct
- **License:** Apache-2.0
- **Finetuned from model:** LLaVA

### Model Sources
- **Dataset:** [SpaceLLaVA](https://huggingface.co/datasets/remyxai/OpenSpaces)
- **Repository:** [VQASynth](https://github.com/remyxai/VQASynth/tree/main)
- **Paper:** [SpatialVLM](https://arxiv.org/abs/2401.12168)


## Citation
```
@article{chen2024spatialvlm,
  title = {SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities},
  author = {Chen, Boyuan and Xu, Zhuo and Kirmani, Sean and Ichter, Brian and Driess, Danny and Florence, Pete and Sadigh, Dorsa and Guibas, Leonidas and Xia, Fei},
  journal = {arXiv preprint arXiv:2401.12168},
  year = {2024},
  url = {https://arxiv.org/abs/2401.12168},
}

@misc{qwen2.5-VL,
    title = {Qwen2.5-VL},
    url = {https://qwenlm.github.io/blog/qwen2.5-vl/},
    author = {Qwen Team},
    month = {January},
    year = {2025}
}
```