Shimakaze (kancolle) - Character

v1.1 (old)
psoft
over 2 years ago

UPDATE: removed noise offset, slightly less training, better for combining with multiple other LoRAs

Finally, after much trial and error, I believe this LoRA came out really well. But you be the judge: let me know what you think and post your own generated images. See features, how to use and examples below.

New features:

  • easy to make good gens on anime models like AOM2 (click "view more" in the gallery to see non cherry-picked batches)

  • compatible with other LoRAs, to fit your style, pose and even use it as an outfit/cosplay for other characters, since you can change hair color

  • works with various models, including anime, 2.5D and realistic (some realistic models may require more tweaking the prompt, weight and CFG to get the best results; see my examples)

How to use:

  • Works with weight 0.6-1.0 and CFG 5-8 , depending on the model (e.g. higher weight and CFG for realistic models)

  • Main trigger word: shimakaze

  • The main trigger word will generally provide the outfit, but these trigger words can be used to emphasize the character/outfit: blonde hair, striped thighhighs, microskirt, elbow gloves, sailor collar, anchor hair ornament, highleg panties, black panties

  • Other keywords associated with the character and context: robot, turret, lifebuoy

Batch grid (same prompts, different seeds, various models)

AOM2

Counterfeit-v2.5

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Info

Version v1.1 (old): 1 File

To download these files, please visit this page from a desktop computer.

About this version: v1.1 (old)

Trained using NeverEnding Dream (NED) (noVae). Trigger words:

"sailor collar, crop top, neckerchief, microskirt, pleated skirt, highleg panties, black panties, striped thighhighs, rabbit ears, elbow gloves, boots"

19 images, handpicked, not cropped. Manually added the same tags plus whatever was different in each (e.g. angle, pose).

10 repeats, 20 epochs, batch size 19.

LR: 0.001, Unet LR: 0.001, Text encoder LR: 0.0005

Net dim: 8, Net alpha: 8

Runtime ~18min

3 Versions

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