Cseti/HunyuanVideo-LoRA-Arcane_Style

v2 Arcane Jinx HunyuanVideo LoRA is released

Advantages:

• Better image quality than the v1

ID Token / Trigger word(s):

Use this in your prompt helps providing the style.

• csetiarcane, scene, character

If you want to generate one or more characters in Arcane style, I strongly recommend including the word 'character' in the prompt as well. This seems to be quite a strong token and helps with displaying the style.

Trainig details:

• LR: 2e-5
• Optimizer: adamw
• epochs: 52
• dataset: 120 (33x704x352) videos
• repeats: 5
• rank: 32
• batch size: 1
• gradient accumulation steps: 4

Arcane Jinx HunyuanVideo LoRA v1

Important Notes:

This LoRA is created as part of a fan project for research purposes only and is not intended for commercial use. It is based on the TV series called Arcane which are protected by copyright. Users utilize the model at their own risk. Users are obligated to comply with copyright laws and applicable regulations. The model has been developed for non-commercial purposes, and it is not my intention to infringe on any copyright. I assume no responsibility for any damages or legal consequences arising from the use of the model.

Compatibility:

• HunyuanVideo

ID Token / Trigger word(s):

Use this in your prompt helps providing the style.

• csetiarcane

Please consider the following:

• With some seeds it doesn't work well, it simply doesn't produce either the style

Acknowledgment:

• Thanks to the Tencent team for making this great model available
• Thanks to tdrussel for the diffusion-pipe that helps us making these LoRAs.
• Thanks to Kijai for his great ComfyUI integration
• Thanks to POM for providing the computing resources. Without this, these LoRAs could not have been created.

Trainig details:

• LR: 1e-4
• Optimizer: adamw
• epochs: 14
• dataset: 135 (33x704x352) videos
• repeats: 5
• rank: 32
• batch size: 1
• gradient accumulation steps: 4

Citation

@misc{kong2024hunyuanvideo,
      title={HunyuanVideo: A Systematic Framework For Large Video Generative Models}, 
      author={Weijie Kong, Qi Tian, Zijian Zhang, Rox Min, Zuozhuo Dai, Jin Zhou, Jiangfeng Xiong, Xin Li, Bo Wu, Jianwei Zhang, Kathrina Wu, Qin Lin, Aladdin Wang, Andong Wang, Changlin Li, Duojun Huang, Fang Yang, Hao Tan, Hongmei Wang, Jacob Song, Jiawang Bai, Jianbing Wu, Jinbao Xue, Joey Wang, Junkun Yuan, Kai Wang, Mengyang Liu, Pengyu Li, Shuai Li, Weiyan Wang, Wenqing Yu, Xinchi Deng, Yang Li, Yanxin Long, Yi Chen, Yutao Cui, Yuanbo Peng, Zhentao Yu, Zhiyu He, Zhiyong Xu, Zixiang Zhou, Zunnan Xu, Yangyu Tao, Qinglin Lu, Songtao Liu, Daquan Zhou, Hongfa Wang, Yong Yang, Di Wang, Yuhong Liu, and Jie Jiang, along with Caesar Zhong},
      year={2024},
      archivePrefix={arXiv preprint arXiv:2412.03603},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03603}, 
}