Add model card for Kiwi-Edit
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by
nielsr HF Staff - opened
README.md
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---
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library_name: diffusers
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pipeline_tag: image-to-video
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---
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# Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance
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Kiwi-Edit is a versatile video editing framework built on an MLLM encoder and a video Diffusion Transformer (DiT). It supports:
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- **Instruction Video Editing**: Modify video content through text prompts.
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- **Reference Image Guidance**: Use a reference image to guide editing for higher visual fidelity and precise control.
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The model synergizes learnable queries and latent visual features for reference semantic guidance, achieving significant gains in instruction following and reference fidelity.
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- **Project Page:** [https://showlab.github.io/Kiwi-Edit/](https://showlab.github.io/Kiwi-Edit/)
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- **Paper:** [Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance](https://huggingface.co/papers/2603.02175)
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- **Repository:** [https://github.com/showlab/Kiwi-Edit](https://github.com/showlab/Kiwi-Edit)
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## Usage
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To use Kiwi-Edit for inference, follow the installation instructions in the [official repository](https://github.com/showlab/Kiwi-Edit). You can run a quick test on a demo video using the following command:
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```bash
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python diffusers_demo.py \
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--video_path ./demo_data/video/source/0005e4ad9f49814db1d3f2296b911abf.mp4 \
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--prompt "Remove the monkey." \
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--save_path output.mp4 --model_path linyq/kiwi-edit-5b-instruct-only-diffusers
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```
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## Citation
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If you use Kiwi-Edit in your research, please cite the following work:
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```bibtex
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@misc{kiwiedit,
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title={Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance},
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author={Yiqi Lin and Guoqiang Liang and Ziyun Zeng and Zechen Bai and Yanzhe Chen and Mike Zheng Shou},
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year={2026},
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eprint={2603.02175},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2603.02175},
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}
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```
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