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README.md
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license: apache-2.0
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---
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license: apache-2.0
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datasets:
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- AIDC-AI/Parrot-dataset
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library_name: transformers
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tags:
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- MLLM
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pipeline_tag: image-text-to-text
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language:
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- en
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---
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# Model Card
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<!-- Provide a quick summary of what the model is/does. -->
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Parrot is a multi-language and multi-modal large language model capable of achieving excellent performance.
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For a comprehensive introduction, please refer to [Parrot Paper](https://arxiv.org/abs/2406.02539) and [Parrot GitHub](https://github.com/AIDC-AI/Parrot).
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# Model Details
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![](https://github.com/AIDC-AI/Parrot/images/teaser.png)
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# Performance
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![](https://github.com/AIDC-AI/Parrot/images/performance.png)
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![](https://github.com/AIDC-AI/Parrot/images/performance_table.png)
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# Usage
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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).
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```markdown
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pip install torch==2.1.2 transformers==4.43.2 pillow==10.3.0
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```
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```python
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import torch
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from PIL import Image
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from transformers import AutoModelForCausalLM
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```
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# Citation
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If you find Parrot useful, please cite the paper
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```markdown
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@article{sun2024parrot,
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title={Parrot: Multilingual Visual Instruction Tuning},
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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},
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journal={arXiv preprint arXiv:2406.02539},
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year={2024}
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}
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```
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# License
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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.
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