Ver NOOB V-PRED V3 EQ

Trained with improved parameters based on NOOB V-PRED EQ VAE exprimental version: https://civarchive.com/models/1858821/noobai-v-pred-10-with-eq-vae

In this version, I removed some trigger words. They are now serparte loras. Only 9 triggerwords left. See the examples first.

I changed the name of this lora to accurately describe its effect. Now it supports the generation of many types of taur.

Most trigger words mean same to the CF-prefix ones. Taurrear means the taur standing on hind legs.

Trigger words explaination for previous versions:

CFback: back view of futanari centaur

CFonelegup: lifting one foreleg pose of futanari centaur

CFstanding: standing pose with all four legs on the ground

CFtwolegsup: lifting two forelegs pose of futanari centaur

CFlying: lying pose of futanari centaur

CFkneeling: kneeling pose of futanari centaur

CFdiphallia: standing pose of a futanari centaur with horse penis and humanoid penis

CFhuman: human taur concept

CFUCup: carrying girl with legs up under the belly of futanari centaur

CFUCdown: carrying girl with legs down under the belly of futanari centaur

CFUCfellatio: carrying girl under the belly of futanari centaur while giving oral

CFdoggy: a futanari centaur has sex with another in doggystyle position

CFmissionary: a futanari centaur has sex with another in missionary position

CFfellatio: a girl/boy is performing fellatio on a futanari centaur

CFreversedoggy: a futanari centaur has sex with another in reversedoggy position

Ver NOOB V-PRED V2.0

Trained based on NOOB V-PRED V1.0 with OneTrainer. See about this version for training details. Changed keywords and added serval concepts.

Ver NOOB V-PRED V1.0

Trained based on NOOB V-PRED V1.0. Change keyword CFundercarriage to CFUC to prevent the appearance of carriages.

Ver NOOB E-PRED V1.0

Trained based on NOOB E-PRED V1.0. Notice that some examples are generated with NOOB V-PRED 0.5.

Updated

Used PonyXL to train this one. Updated dataset to achieve better performance. It enhanced this concept on PonyXL and related models. See the examples first.

Typo issue solved. Now undercarriage is correctly spelled.

Fur color issue solved. See the examples.

Please be sure to use trigger words and hires.fix in generation. Some of triggerwords seems to overbake the images or bring bad styles when upweighting them. Reason may be I used 3d images when training. Use highres.fix to prevent this from happening.

Adding concepts: doggy, diphallia, undercarriage

About V2.0

In this version, finally I have different poses with weighted cation. Also with multires technque.

Updated keywords will prevent the models from misreading the tokens like kneeling, standing, etc.

Currently now have five keywords for different poses:

CFFB: back to the viewer;

CFKN: kneeling;

CFLU: two legs up;

CFLY: lying

CFST: standing or with single leg up.

The bad thing is, still, prompt is not sensitive, and many times the penis will mistaken for hooves or the centaur having multiple legs. You can use some horse penis lora to improve it. But it still needs dozens of trials.

Recommend using highres fix with good seeds to generate good images.

WORKS BADLY IN 512X512

Multires technique parameter:

multires_noise_iterations="6"

multires_noise_discount=0.3

Introduction

This LyCORIS is used to generate futanari centaur.

How to use it

I recommand using it in weight 0.7-0.8. It works well with other loras. But sometimes the cock will be mistaken for hooves.

Training details

Traingset is of about 220 images. They are mirrored before training. Half of them are chosen as regularization images. Total steps are about 15000.

I divided the training set into 5 subsets and tag the gesture. It is to control the results. But it didn't work, sad. If you want to give it a try, the trigger tags is the folder name below.

Regularization = true

resolution=512

batch_size=2

epoch=10

network_dim=32

network_alpha=32

clip_skip=2

Using AdamW8bits as optimizer:

• lr="1e-4"

• unet_lr="1e-4"

• text_encoder_lr="1e-5"

Locon parameters:

• conv_dim=4

• conv_alpha=4