DaSiWa WAN 2.2 I2V 14B Lightspeed TeasingKiss High
27
1
18
27 1 18
🛠️ Recommended Settings
Steps: 4
CFG: 1
Sampler/Scheduler: Euler/Normal or UniPC/Simple
Resolution up to 720p (native quality).
My go to settings:
Aspect ratio 3:4 (784x1136) or 9:16 (720x1264)
CFG 1
Euler/Normal
4 steps
16 fps
Sigma Shift: 5
Add other LoRAs with 0.6-1
16 fps, 81 frames ~ 5s
VAE: Wan 2.1 VAE
CLIP: umt5_xxl_fp8_e4m3fn_scaled
💫 Speed + Examples
On 16GB VRAM, 64GB RAM, 4 steps, cfg 1, 81 frames
480 pixel side length (384x576): 70-90 sec
720 pixel side length (592x848): 120-140 sec
768 pixel side length (576x1008): 3 min
896 pixel side length (672x1184): 6 min
960 pixel side length (784x1136): 9-11 min
All examples are without any additional LoRAs
Initial example images made by me are made with my model 🗡️💀 DaSiWa-Illustrious-XL 💀🗡️
Some initial examples are borrowed - 🖤 the creators for their awesome art! 😊
🩻 Known issues
Tell me 🫵🫢
🩺 Fixes & Feedback
If you use LoRAs, try to respect the LoRA training triggers and try some versatile descriptions, most LoRAs will work with 0.6-1.2 (start with 1.0)
Do not mass add LoRAs, just add 1 or 2 (x2 High+Low)
Negative prompting do not work with cfg 1, thats a limitation of speed-ups with cfg 1
Low resolution (e.g.384x576) are only for fast samples and will blur fine details, do a higher resolution if you want clear details
模型信息
'%3e%3cg%3e%3cpath d='M6.9375%2c1.875L14.8125%2c1.875C15.5374%2c1.875000858307%2c16.125%2c2.462627%2c16.125%2c3.1875L16.125%2c11.0625C16.125%2c11.78737%2c15.5374%2c12.375%2c14.8125%2c12.375L6.9375%2c12.375C6.21263%2c12.375%2c5.625%2c11.78737%2c5.625%2c11.0625L5.625%2c3.1875C5.625%2c2.462626%2c6.21263%2c1.875000343323%2c6.9375%2c1.875ZM6.9375%2c3C6.83395%2c3%2c6.75%2c3.0839499999999997%2c6.75%2c3.1875L6.75%2c11.0625C6.75%2c11.16605%2c6.83395%2c11.25%2c6.9375%2c11.25L14.8125%2c11.25C14.9161%2c11.25%2c15%2c11.16605%2c15%2c11.0625L15%2c3.1875C15%2c3.0839499999999997%2c14.9161%2c3%2c14.8125%2c3L6.9375%2c3ZM11.25%2c13.5C11.25%2c13.1893%2c11.50184%2c12.9375%2c11.8125%2c12.9375C12.1232%2c12.9375%2c12.375%2c13.1893%2c12.375%2c13.5L12.375%2c14.8125C12.375%2c15.5374%2c11.78737%2c16.125%2c11.0625%2c16.125L3.1875%2c16.125C2.462626%2c16.125%2c1.875000171661%2c15.5374%2c1.875%2c14.8125L1.875%2c6.9375C1.875%2c6.21263%2c2.462626%2c5.625%2c3.1875%2c5.625L4.5%2c5.625C4.81066%2c5.625%2c5.0625%2c5.87684%2c5.0625%2c6.1875C5.0625%2c6.49816%2c4.81066%2c6.75%2c4.5%2c6.75L3.1875%2c6.75C3.0839499999999997%2c6.75%2c3%2c6.83395%2c3%2c6.9375L3%2c14.8125C3%2c14.9161%2c3.0839499999999997%2c15%2c3.1875%2c15L11.0625%2c15C11.16605%2c15%2c11.25%2c14.9161%2c11.25%2c14.8125L11.25%2c13.5Z' fill='%239DA2A8' fill-opacity='1' style='mix-blend-mode:passthrough'/%3e%3c/g%3e%3c/g%3e%3c/svg%3e)
🛠️ Recommended Settings
Steps: 4
CFG: 1
Sampler/Scheduler: Euler/Normal or UniPC/Simple
Resolution up to 720p (native quality).
My go to settings:
Aspect ratio 3:4 (784x1136) or 9:16 (720x1264)
CFG 1
Euler/Normal
4 steps
16 fps
Sigma Shift: 5
Add other LoRAs with 0.6-1
16 fps, 81 frames ~ 5s
VAE: Wan 2.1 VAE
CLIP: umt5_xxl_fp8_e4m3fn_scaled
💫 Speed + Examples
On 16GB VRAM, 64GB RAM, 4 steps, cfg 1, 81 frames
480 pixel side length (384x576): 70-90 sec
720 pixel side length (592x848): 120-140 sec
768 pixel side length (576x1008): 3 min
896 pixel side length (672x1184): 6 min
960 pixel side length (784x1136): 9-11 min
All examples are without any additional LoRAs
Initial example images made by me are made with my model 🗡️💀 DaSiWa-Illustrious-XL 💀🗡️
Some initial examples are borrowed - 🖤 the creators for their awesome art! 😊
🩻 Known issues
Tell me 🫵🫢
🩺 Fixes & Feedback
If you use LoRAs, try to respect the LoRA training triggers and try some versatile descriptions, most LoRAs will work with 0.6-1.2 (start with 1.0)
Do not mass add LoRAs, just add 1 or 2 (x2 High+Low)
Negative prompting do not work with cfg 1, thats a limitation of speed-ups with cfg 1
Low resolution (e.g.384x576) are only for fast samples and will blur fine details, do a higher resolution if you want clear details