Correct pipeline tag and add library name
Browse filesThis PR corrects the `pipeline_tag` to `image-to-text` which more accurately reflects the model's functionality (image input, text output). It also adds the `library_name` as `transformers` since the provided code snippets utilize the transformers library.
README.md
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pipeline_tag:
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# VisualQuality-R1-7B
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This is the latest version of VisualQuality-R1, trained on a diverse combination of synthetic and realistic datasets.<br>
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> The first NR-IQA model enhanced by RL2R, capable of both quality description and rating through reasoning.
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<img src="https://cdn-uploads.huggingface.co/production/uploads/655de51982afda0fc479fb91/JZgVeMtAVASCCNYO5VCyn.png" width="600"/>
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## Quick Start
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This section includes the usages of **VisualQuality-R1**.
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file_name = "output.txt"
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with open(file_name, "w") as file:
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for key, value in path_score_dict.items():
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file.write(f"{key} {value}
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print("Done!")
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```
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```
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</details>
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## Related Projects
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- [ECCV 2024] [A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment](https://arxiv.org/abs/2403.10854v2)
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- [CVPR 2025] [Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption](https://www.arxiv.org/abs/2503.11221)
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## 📧 Contact
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If you have any question, please email `wth22@mails.tsinghua.edu.cn` or `tianhewu@cityu.edu.hk`.
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## BibTeX
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```
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@article{wu2025visualquality,
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author={Wu, Tianhe and Zou, Jian and Liang, Jie and Zhang, Lei and Ma, Kede},
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journal={arXiv preprint arXiv:2505.14460},
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year={2025}
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}
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```
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---
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base_model:
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- Qwen/Qwen2.5-VL-7B-Instruct
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language:
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- en
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license: mit
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pipeline_tag: image-to-text
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library_name: transformers
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tags:
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- IQA
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- Reasoning
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- VLM
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- Pytorch
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- R1
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- GRPO
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- RL2R
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---
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# VisualQuality-R1-7B
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This is the latest version of VisualQuality-R1, trained on a diverse combination of synthetic and realistic datasets.<br>
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> The first NR-IQA model enhanced by RL2R, capable of both quality description and rating through reasoning.
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<img src="https://cdn-uploads.huggingface.co/production/uploads/655de51982afda0fc479fb91/JZgVeMtAVASCCNYO5VCyn.png" width="600"/>
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## Quick Start
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This section includes the usages of **VisualQuality-R1**.
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file_name = "output.txt"
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with open(file_name, "w") as file:
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for key, value in path_score_dict.items():
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file.write(f"{key} {value}
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")
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print("Done!")
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```
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```
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</details>
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## Related Projects
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- [ECCV 2024] [A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment](https://arxiv.org/abs/2403.10854v2)
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- [CVPR 2025] [Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption](https://www.arxiv.org/abs/2503.11221)
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## 📧 Contact
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If you have any question, please email `wth22@mails.tsinghua.edu.cn` or `tianhewu@cityu.edu.hk`.
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## BibTeX
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```
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@article{wu2025visualquality,
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author={Wu, Tianhe and Zou, Jian and Liang, Jie and Zhang, Lei and Ma, Kede},
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journal={arXiv preprint arXiv:2505.14460},
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year={2025}
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}
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