Miyamoto Rei (HOTD) - Character

v1.0
psoft
over 2 years ago

LoRA trained with images of character Miyamoto Rei (High School of the Dead)

v1.5 (NEW)

Increased dataset, modified tags, cleaned up tags, used new and improved training parameters. This results in a both more consistent and flexible LoRA. It works with more models and can be combined with other LoRAs. The example images combine with another character LoRA.

-- previous versions --

v1.5

New training parameters, tags and dataset. Trained on NAI. Tested on AOM2, Perfect World, NeverEnding Dream, and other models. Works with 1.0 weight and 0.3-0.7 CFG, but depends on the model.

You don't need a trigger word to get the character. For the basic uniform you can simply use the trigger "serafuku". You can also add to the positive or negative prompt to get variations from the tagged training data: shirt, skirt, thighhighs, elbow pads, knee pads, sneakers, rifle, stick, blood, torn clothes, shoulder holster.

See the information in the image examples, including for tested models.

Works with multiple models and LoRAs.

v1.0

Better results with 0.5-0.7 weight and 0.3-0.6 CFG (v1.0), but it may depend on the model used.

Works with realistic and anime models and to work with other characters and styles (see examples on how to achieve this). Clothes can be changed by adding, removing or reordering these tags:

"green sailor collar, black bow, green skirt, black thighhighs, long sleeves, brown hair, brown eyes, hair between eyes, ponytail, sneakers, white footwear"

(tip: don't describe the shoes if you don't want a full body image)

See the version information for more on the LoRA training. Please post your images and let me know your feedback.

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Info

Version v1.0: 1 File

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

About this version: v1.0

Trained using NeverEnding Dream (NED) (noVae).

20 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 20.

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

Net dim/alpha: 8

3 Versions

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