| # Model Card | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| Parrot is a multi-language and multi-modal large language model capable of achieving excellent performance. | |
| For a comprehensive introduction, please refer to [Parrot Paper](https://arxiv.org/abs/2406.02539) and [Parrot GitHub](https://github.com/AIDC-AI/Parrot). | |
| # Model Details | |
|  | |
| # Performance | |
|  | |
| # Usage | |
| Below is a code snippet to run Parrot with multimodal inputs. For additional usage instructions, including inference wrapper and Gradio UI, please refer to [Parrot GitHub](https://github.com/AIDC-AI/Parrot). | |
| ```markdown | |
| pip install torch==2.1.2 transformers==4.43.2 pillow==10.3.0 | |
| ``` | |
| ```python | |
| import torch | |
| from PIL import Image | |
| from transformers import AutoModelForCausalLM | |
| ``` | |
| # Citation | |
| If you find Parrot useful, please cite the paper | |
| ```markdown | |
| @article{sun2024parrot, | |
| title={Parrot: Multilingual Visual Instruction Tuning}, | |
| author={Sun, Hai-Long and Zhou, Da-Wei and Li, Yang and Lu, Shiyin and Yi, Chao and Chen, Qing-Guo and Xu, Zhao and Luo, Weihua and Zhang, Kaifu and Zhan, De-Chuan and others}, | |
| journal={arXiv preprint arXiv:2406.02539}, | |
| year={2024} | |
| } | |
| ``` | |
| # License | |
| The project is licensed under Apache License Version 2.0 and is restricted to uses that comply with the license agreements of Qwen and Clip. | |