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An unofficial character LoRA for
Aqua
from
KonoSuba: God's Blessing on This Wonderful World!
, trained on
waiIllustriousSDXL v17
(commonly saved as
waiIllustriousSDXL_v170
). This repository includes every unique epoch file from two resume rounds. Comparative evaluation recommends
R2E6
(
aqua_rE5S846-000006.safetensors
) as the default, at strength
0.8
. The training images and captions are in
abbuibuibui/Aqua-Dataset
.
This is a fan-made derivative, not an official product. Rights to the character and source work remain with their respective owners.
Files
Unnumbered finals are
not
SHA-256 duplicates of the numbered epoch next to them, so every file below is kept.
Label
File
Role
R1E1
aqua-000001.safetensors
Alternate. Round 1: white dress renders mint green.
R1E2
aqua-000002.safetensors
Alternate. Round 1: angry portrait.
R1E3
aqua-000003.safetensors
Alternate. Round 1: muddy hair on the face crop.
R1E4
aqua-000004.safetensors
Alternate. Usable identity; entered the weight matrix. White dress still mint at 0.8.
R1Final
aqua.safetensors
Alternate. Unique SHA vs E4. Hair bobbles weaker on the face crop.
R2E5
aqua_rE5S846-000005.safetensors
Alternate. Close to R2E6; entered the matrix.
R2E6
aqua_rE5S846-000006.safetensors
Recommended default.
Best balance of portrait, standard goddess dress, white gown, sitting, and night street at 0.8.
These images are direct
R2E6 @ 0.8
outputs with no retouching. Settings: Euler a, 28 steps, CFG 4.5, CLIP skip 2,
832×1216
; Hires and ADetailer were off.
Portrait
Standard outfit
White dress
Night street
Trigger Words and Settings
This LoRA has an identity trigger
and
outfit tokens. Captions used
keep_tokens = 2
.
Role
Token
Typical look
Identity
aqua_konosuba
Long blue hair, blue eyes, hair bobbles, large hair bow
Outfit
aqua_konosuba_standard_outfit
Blue goddess dress, detached sleeves, thighhighs, green bow
Outfit
aqua_konosuba_white_dress
White off-shoulder gown
Outfit
aqua_konosuba_travel_cloak
Travel cloak looks from the set
Outfit
aqua_konosuba_sleepwear
Sleepwear stills from the set
Recommended: waiIllustriousSDXL v17 or an Illustrious / NoobAI-family model; LoRA strength
0.8
(0.4 already identifies her but the white dress stays mint; 1.0 often crops the collar off close-ups); Euler a, 28 steps, CFG 4.5, CLIP skip 2,
832×1216
.
If ADetailer is enabled on the face, put
aqua_konosuba
plus long blue hair, blue eyes, and hair bobbles in the face prompt.
Example:
<lora:aqua_rE5S846-000006:0.8>,
masterpiece, best quality, very aesthetic, absurdres, anime screencap,
1girl, solo, aqua_konosuba, aqua_konosuba_standard_outfit,
long blue hair, blue eyes, hair bobbles, large hair bow,
full body, looking at viewer, outdoors
Negative prompt:
lowres, bad, bad anatomy, bad hands, text, error, missing fingers, extra digit,
fewer digits, cropped, worst quality, low quality, signature, watermark,
username, blurry, extra person, two girls, multiple girls,
blonde hair, pink hair, red hair, brown hair, green eyes, purple eyes, black hair
Why R2E6
All eight unique checkpoints were first screened at strength 0.8 with the same recipe and fixed seeds on a front portrait, a standard-outfit full-body shot, and a white-dress full-body shot. Early R1 files missed the white gown or the face. Only
R2E5 / R2E6 / R1E4
advanced.
The second round generated one image per candidate in 10 fixed scenes at 4 strengths (0.4 / 0.6 / 0.8 / 1.0):
120
direct outputs.
Candidate
Observed result
Decision
R2E5
Nearly the same as R2E6.
Alternate.
R2E6
Most consistent identity across portrait, standard dress, white gown, sitting, and night tests at 0.8.
Recommended default at 0.8.
R1E4
Standard outfit usable; white dress still mint at 0.8.
Data: 60 manually selected Aqua stills with matching
.txt
captions. Captions start with
aqua_konosuba, <outfit>
,
keep_tokens = 2
, remaining tags shuffled. Outfit counts: standard 40 / white dress 8 / travel cloak 7 / sleepwear 5. Published as
abbuibuibui/Aqua-Dataset
.
Network: LoRA rank 32 / alpha 16, UNet plus both text encoders.
Optimizer: AdamW8bit; UNet LR
1e-4
, text-encoder LR
5e-5
; cosine schedule.
Precision and resolution: bf16, 1024 buckets, batch size 1, latents cached to disk, sdpa,
no_half_vae
. Flip and color augmentation off.
Steps: repeat 3 per image, 7 epochs per round. The last resume (
aqua_rE5S846
) ran
1260
optimizer steps (60 × 3 × 7). Learning-rate values come from the shared kink-panel trainer command, not from a printed LR line in
train.log
.
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