Wan-LoRA-Arcane-Jinx-v1

Wan-LoRA-Arcane-Jinx-v1

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Trainig details:

This LoRA was trained on RunPod cloud GPUs. I tried a method where I first trained the LoRA on images only and then after a certain number of steps continued training only on videos.

• LR: 2e-5
• Optimizer: adamw_optimi
• epochs: 15 (image) + 7 (video)
• steps: 2550 (image) + 2520 (video)
• dataset: 33 images and 35 videos
• repeats: 10
• rank: 128
• batch size: 2
• gradient accumulation steps: 1

For training I used the Diffusion-Pipe repo.

Inference

It seems, the model likes long descriptive prompts. Look at the attached videos for prompt examples. Based on my tests if you use short prompts, the lora effect is weak.

For inference I recommend:

• ComfyUI native nodes
• Kijai's ComfyUI wrapper nodes

<b>Trigger words</b>: csetiarcane, Nfj1nx, blue hair

(If it isn't enough so you don't get the style/character, I recommend adding "animation style" to you prompt. It can help providing the style but in some cases the result will be too cartoony)

<b>Strength</b>: 0.9-1.0

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.

Acknowledgement

Special thanks to Kijai for the tireless and excelent work done for the community to enable us to use these solutions as soon as possible, as well, as to Comfyanonymous for implementing them so quickly with such a good quality natively into ComfyUI, and also to TDRussel for making LoRA training available to the community so quickly.

Support

Producing and sharing this kind of open-source work requires renting cloud GPUs, which gets expensive quickly. If you find it useful and would like me to keep contributing, your support is very much appreciated: