Training Details:

Utilizing a large dataset of 22,000 images sourced from hypnohub, this LoRA focuses on a variety of hypnosis-related themes.

2xT4 on Kaggle, 30gb vram in total. ~15 hrs training time, 8 epochs. "I forgot the number but it's B I G" steps.

Used code from Hollowstrawberry's Google Colab repo, modified, and adapted to Kaggle by me. Kaggle repo (code is a complete mess), find the Training SDXL Lora on Kaggle.ipynb file and import it into Kaggle.

All dim alpha values was set to 24.

Optimiser: Prodigy

Scheduler: REX

Batch size: 6 (3 per gpu)

Grad. acc. steps: 1

Additionally used IP noise = 0.1; Prodigy 1.1.2 "slice_p=11" arg; --debiased_estimation_loss

Dataset:

The training dataset consists of ~20k images scraped from hypnohub, all centered around hypnosis and related concepts. For a full list of tags used in the dataset, you can refer to the Bottom of the Tag Guide section where you can find a Gist link.

Dataset was scraped from hypnohub with this prefill filtering:

-manip,-animated,-animated_gif,-voice_acted,-animated_eyes_only,-tagme,-traditional,-sketch,-meme,-ai_art,-caption,-caption_only,-fascinum,-3d_custom_girl

All images was downscaled to 1024 (bigger side) pixels by lanczos method in XnConvert tool.

My booru scraper script also gathering tags from site. After additional filtering (see below), further tagging with JoyTag (high confidence like 0.6) in the Dataset Helpers tool.

Additionally some further filtering were applyed:

"score:>x" tag, where x value is defined by me for every main tag.
Aspect Ratio filtering: for every image were calculated Aspect Ratio value (for example value for AR 16x9 will be 1.77), and images that were too long or wide (with an AR value greater than 3) were filtered out.

After filtering and tagging, tags in each .txt file was organized by this metod:

[Concept tags] = always first in the file, sorted a-z.

[Style tags] = not sorted, simply moving them after Concept tags.

[Main tags] = [Concept tags] + [Style tags]. The number of main tags is calculated. This is our keep_tokens value.

After these steps, .txt files looking like this: [Main tags], other tags. Then all pairs of .txt + .img were sorted by keep_tokens value. Finally, I got a folder structure whose name depended on the keep_token value (i.e. 1, 2, 3, etc.).

Tagging Guide:

To utilize Mesmera effectively, you can explore a range of styles and concepts. Here are list of the main tags I was focused on:

Meta:

femsub: 700 <-- female submissive. use it to specify on whom chosen hypnotic effect will be applied
before_and_after: 676
pov_sub: 557 <-- Point of view of submissive character
sequence: 539 <-- can be used either as sequence of transformations of given character or just comic-style sequence
see-through: 468 <-- contextually aware, i think...
malesub: 426 <-- male submissive. same as femsub
maledom: 309 <-- male dominant. use it to specify who is applying effects on fem/male sub.
gameplay_mechanics: 289 <-- idk what is that, but it should help with some interfaces or level bars shit i guess
femdom: 270 <-- female dominant. same as maledom
pet_play: 222

Concepts:

kaa_eyes: 700
happy_trance: 698
bimbofication: 683
hypnotized_hypnotist: 680
transformation: 553 <-- random transformations in training data, can help can make things worse
breast_expansion: 512 <-- warying breast size, depends on artist style
hypnotic_audio: 493
haigure: 480
dronification: 460 <-- warying results, general non-specific tag
evil_smile: 444
hypnotic_screen: 435
bodysuit: 417
hypnotic_app: 415
tech_control: 402 <-- warying results, general non-specific tag
control_indicator: 400
robotization: 365
clothed_exposure: 359
visor: 355
progress_indicator: 331
hypnotic_accessory: 329
lip_expansion: 326
zombie_walk: 316
hypnotic_music: 311
pendulum: 311
mantra: 304
altered_perception: 300 <-- use with "thought bubble" tag
enemy_conversion: 291
hypnotic_eyes: 279
hypnotic_gas: 271
charm_(spell): 271
empty_eyes: 270
hypnotic_breasts: 269
electricity: 268
barcode: 266
hypnotic_penis: 262
hypnotic_light: 259
confused: 259
corruption: 242
chicken_pose: 235
spiral_eyes: 228
unhappy_trance: 212
shrunken_irises: 203
glowing_eyes: 201
hypnotic_beam: 184
standing_at_attention: 182
latex: 178
self_hypnosis: 176
housewife: 167
stage_hypnosis: 160
aura: 160
hypnotic_tentacle: 154
eye_roll: 152
hypnotic_ass: 139
harem_outfit: 132
hypnotic_feet: 129
asphyxiation: 103

Characters:

erika_(er-ikaa): 510
kaa: 315
crystal_(zko): 226
hypno-tan: 162
kassidy_(medrifogmatio): 134
mrs._erickson_(zko): 59

Styles:

sleepymaid: 624
jimryu: 512
darkhatboy: 345
oo_sebastian_oo: 331
hadant: 308
mythkaz: 267
nexus_light: 253
lairreverenteboladepelos: 243
etlabsotwe: 234
polmanning: 223
zko: 214
brellom: 200
katsiika: 199
onefeefoor: 196
eroborne: 196
zephyrgales: 177
mahoumonsterart: 177
apopop: 176
shishikasama: 174
smeef: 171
faetomi: 170
dochaunt: 167
porniky: 165
djuuicebox: 164
enetheligthingdancer: 160
ryuugu: 158
brushie_art: 152
efalabrino: 151
eshie: 151
glowhorn: 151
cursedrooks: 150
myuk: 150
psyfly: 148
4headboiii: 148
b-ginga: 144
detritus: 143
medrifogmatio: 137
artofadam: 127
batta18th: 126
ghostec: 126
gmun: 125
keeper_of_pots: 125
idpet: 123
horiizyn: 122
pstash: 122 <-- not working
tomo86: 119
supercasket: 118
ameerashourdraws: 115
tunberuku: 113 <-- 50/50, dirty dataset
httpwwwcom: 112
electrickronos: 112
erocoffee: 109
abarus: 109
yumiiart: 108
wrenzephyr2: 108
foolycooly: 108
lapislazuliart: 105
zelhypno: 105 <-- 50/50, why? idk :(
supersatanson: 103
vahn_yourdoom: 101
zorro-zero: 100
yensh: 97
davidthewolfx10: 94
zombi62: 94
maozi_dan: 89
jostony24k0: 88
rosvo: 83
alerith: 82
reliusmax: 81
m4ns0n: 81
konaloid: 80
maynara: 80
sakurarose12: 79
sweetlittleneko: 78
malberrybush: 74
harvestman_here: 70
kronobas28: 68
orphan2: 68
syas-nomis: 63
zelamir: 62
nettleseeds: 61
4five1: 61
the_iron_mountain: 56
kibazoku: 55
cavitees: 55
sl33pyg1mp: 55
shozaya: 54
gerph: 50
blueparikeet: 49
drevod: 48
shieol1: 46
hmage: 45
konno_tohiro: 45
rnslivr: 44
deepspaceart: 42
singlesalt: 40
magukappu: 39
borvar: 38
glatu: 38
cuddlesword: 36
nez-box: 36
terasu_mc: 36
strwbrrychz: 35
thiccwithaq: 35
a_singular_fish: 33
hentai_man: 32
chien_vietnam: 32
alittleshyart: 30
rind_rin00: 28
slugbox: 24

Full list of tags in the Mesmera's training dataset can be found in this Gist.

Mesmera v1 Gist links:

Tagging guide: Gist.

Full list of dataset tags: Gist.

Roadmap (kinda):

So... This LoRA is mostly working, but I'm still not satisfied with several quality aspects (for example, it was trained at 512 resolution). I will likely release Mesmera v2.5 this year, though I don't know exactly when. I feel slightly burnt out by this project, and I'm not going to push myself into it any further. I will focus on small-effort LoRAs for now. (27.03.25)

After I release Mesmera v2.5 for Illustrious 0.1, I will likely follow this training plan:

NoobAI Eps
NoobAI V-pred
Pony v6

And after Pony I will mostly handling user requests:

Training for other models on the SDXL architecture: IL 1.1, IL 2.0/3.0 (hopefully), RouWei, Hassaku, WAI, etc.
I will also try to train for Flux, Lumina, SD1.5, SD3.5, and Sana.
Additionally, I will try to experiment with realistic style fine-tunes (Illustrious, Pony).

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