Any-to-Any
Transformers
Safetensors
qwen3_5
image-text-to-text
video-editing
agent
tool-use
long-horizon
reinforcement-learning
qwen3.5
Instructions to use tencent/WeVisCut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/WeVisCut with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("tencent/WeVisCut") model = AutoModelForMultimodalLM.from_pretrained("tencent/WeVisCut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## Citation
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```bibtex
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@misc{
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```
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## Citation
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```bibtex
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@misc{mu2026weviscuteditingroomagent,
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title={WeVisCut: The Whole Editing Room in One Agent From Narration to Long-Form Video},
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author={Chenyu Mu and Wenming Weng and Qinrui Wang and Xingsong Ye and Hao Yu and Jun He and Chong Sun and Chen Li and Jing Lyu and Erkun Yang and Cheng Deng},
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year={2026},
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eprint={2610.38352},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2610.38352},
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}
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```
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