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Ainz Ooal Gown LoRA

Description

Low Rank Adaptation for Ainz Ooal Gown from the Overlord series.

Light Novel A reference image from the light novel. See other references for the anime/manga in the references folder

Usage

If using Stable Diffusion WebUI:

  1. Download AinzOoalGownLoRA.safetensors
  2. Copy and paste into stable-diffusion-webui/models/Lora
  3. Use the trigger word <lora:AinzOoalGown:0.8> in the prompt. Works best with weights ranging from 0.5 to 0.8 (default is 1)

Examples

The Good

The Good Loses some likeness of the original character, but retains that cool skeletal undead look. See more (good) examples in the examples folder

Parameters:

Prompt: 1boy, (overlord, lich, skeleton, skull, bone, ainz ooal gown:1.2), (best quality:1.2), (masterpiece:1.2), (highres:1.2), extremely detailed, illustration, solo, (looking at viewer:1.2), (sharp focus:1.5), (masterpiece illustration:1.5), light particles, glowing light, lens flare, <lora:AinzOoalGown:0.8>

Negative prompt: EasyNegative, worst quality, low quality, normal quality, blurry, deformed, disfigured, morbid, mutated, bad anatomy, bad art, lowres, polar lowres, bad face, bad hands, bad body, bad feet, bad proportions, bad leg, more legs, gross proportions, poorly drawn, (text:1.5), error, missing fingers, missing arms, missing legs, short legs, extra digit, 2girls, 1girl, long skirt, indoors, out of frame, only upper body, only lower body, petite, print, chibi, only head

Steps: 30, Sampler: DDIM, CFG scale: 7, Seed: 4149917258, Size: 512x512, Model hash: 89d59c3dde, Model: nai

The Bad

The Bad Still interesting, but misshapen

The Ugly

The Ugly It kinda looks like him if you squint

Training Details

  • Training Model: Anything V3.1
  • Training Dataset: 13 images
  • Training Repeats: 10
  • LoRA Network Linear Dimension: 32
  • LoRA Network Linear Alpha: 16
  • Optimizer: AdamW8bit
  • UNet Learning Rate: 1e-4
  • Text Encoder Learning Rate: 5e-5
  • Learning rate warmup steps: 0
  • Learning rate Scheduler: constant
  • Sampler: ddim
  • Epochs: 10
  • Training Batch Size: 6
  • Precision: fp16 Mixed
  • Clip Skip: 2
  • Gradient Accumulation Steps: 1
  • Total Steps: 230
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