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----
-license: mit
----
-
-The model corresponds to [Compare2Score](https://compare2score.github.io/).
-
-## Quick Start with AutoModel
-
-<!-- For this image, ![](https://raw.githubusercontent.com/Q-Future/Q-Align/main/fig/singapore_flyer.jpg) start an AutoModel scorer with `transformers==4.36.1`:
- -->
-```python
-import requests
-import torch
-from transformers import AutoModelForCausalLM
-
-model = AutoModelForCausalLM.from_pretrained("q-future/Compare2Score", trust_remote_code=True, attn_implementation="eager", 
-                                             torch_dtype=torch.float16, device_map="auto")
-
-from PIL import Image
-image_path_url = "https://raw.githubusercontent.com/Q-Future/Q-Align/main/fig/singapore_flyer.jpg"
-print("The quality score of this image is {}".format(model.score(image_path_url)) 
-```
-
-## Evaluation with GitHub
-```shell
-git clone https://github.com/Q-Future/Compare2Score.git
-cd Compare2Score
-pip install -e .
-```
-
-```python
-from q_align import Compare2Scorer
-from PIL import Image
-
-scorer = Compare2Scorer()
-image_path = "figs/i04_03_4.bmp"
-print("The quality score of this image is {}.".format(scorer(image_path)))
-```
-
-## Citation
-
-```bibtex
-@article{zhu2024adaptive,
-  title={Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare},
-  author={Zhu, Hanwei and Wu, Haoning and Li, Yixuan and Zhang, Zicheng and Chen, Baoliang and Zhu, Lingyu and Fang, Yuming and Zhai, Guangtao and Lin, Weisi and Wang, Shiqi},
-  journal={arXiv preprint arXiv:2405.19298},
-  year={2024},
-}
-```