Wan2.2 - Korean Women

2025-08-26

Alright, so after releasingSeoullina v2.0, I've spotted a few problems.

The biggest issue is a bug that causes the breast physics to bounce around even when the character is completely still.

I can't tell you how hard I laughed when I first saw it.😂😂

My guess is that it happens on heavily quantized models, at low resolutions, or when cleavage is exposed, but I totally missed it. For this issue, please refer to the video that kyo55966933uploaded to the gallery (and thanks for the video!)

I'm going to investigate the issue and prepare for version 2.1.

2025-08-24

First, a huge thank you to everyone who has been sharing their work in the gallery. The results are absolutely fantastic!

For Seoullina v2.0, I've made some important updates to the training process.

Previously, my preferred method was to train only the low-noise model and use the Wan 2.1 Self-forcing LoRA at a high strength (e.g., 2). This produced great image quality, But I now believe the high strength was a major contributor to the deforming issue.

However, I've found an approach that yields better results. By training both the High/Low models together and using the Wan 2.2 Self-forcing LoRA(link1, link2), the deforming issue has been significantly improved.

The training dataset has also been revised.

It came to my attention that the less realistic skin texture from images generated by Flux was sometimes undesirable. To address this, I've updated the dataset, which has resulted in the character's appearance now being different from the v1.0.

As the original goal is to create a fictional character, I believe this change is a positive step forward.

Recommendations

The Wan 2.2 Self-forcing LoRAs (High/Low) are required!

Sampler: euler

Scheduler: beta

Shift: 8+

Steps: 4+

CFG: 1?

2025-08-11

The Busansuji version has been released.

In the Seoullina v1.0, there was a deforming issue.

I wanted to fix it, but I couldn't find the exact cause, as it occurred even when training both the high and low models.

For the Busansuji v1.0, I've selected a model that should minimize this problem.

I'll continue to experiment with different approaches to find the best dataset configuration.

For the Self-forcing LoRA, I suggest using the wan 2.1 64-rank model(https://civitai.com/models/1585622?modelVersionId=2014522).

And set the strength to 2 for the high model and 1 for the low model.

Also, using the euler sampler is recommended for the best results.

About This LoRA

First off, I used the Diffusion-pipe for the training.

I really want to say thank you to tdrussell for updating the tool so fast, right after Wan 2.2 came out.

I made a total of 206 images with the Flux.D model and did my best to include many different conditions.

For example, I used various lighting like day, night, indoor, and club scenes, and the shots were a mix of close-ups, medium, and full shots.

But, I know it's lacking when it comes to camera angles.

It's a shame that I couldn't put together data with more varied angles.

However, I think the camera movement in the new wan2.2 model is better, so I believe this will overcome that weak spot.

Usage

Please use the LoRA as both the High and Low model LoRA.