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SSJ4_SDXL
Super Saiyan 4
v3_Anime
Anime v1.0
v1.0
Caulifla + Super Saiyan 4 Form (Dragon Ball) [SDXL & SD1.5]

Caulifla + Super Saiyan 4 Form (Dragon Ball) [SDXL & SD1.5]

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#애니메이션
#캐릭터
#여성
#dragon ball
#dragon ball super
#어디 남자
#girls
#dragon ball gt
#SDXL
#sdxl anime
#ssj4
#sdxl character
#citron sdxl

New Version: SSJ4 SDXL

My first success with an SDXL Lora. Please let me know what you think!

As with last time I'll give 200 buzz to the first 10 people that post a picture on this SDXL Lora. (Limit 200 buzz per account)

Also if you have any SDXL training advice or checkpoints you think I should use for image generation please let me know! I'd prefer a more anime and less realistic style if possible.

I don't have a strong enough GPU for SDXL so I have to use TensorArt's website to generate all the images so the generation data might be a bit messed up :(


I'll give 200 buzz to the first 10 people that post a picture on my Super Saiyan 4 Caulifla Lora. (Limit 200 buzz per account) All Ten posts are taken! Thank you everyone!

Also there is a 2000 Buzz image creation bounty for this Super Saiyan 4 Caulifla Lora here:

https://civitai.com/bounties/589 - Bounty is over. Thanks to the participants and congrats to the winner!


Version 4 SUPER SAIYAN 4 update!

Please considering listening to Ka Ka Kachi Daze on Youtube when you use this for the first time.

Caulifla's SSJ4 supports a bunch of random changes. I gave her a black tube top and also a black jacket in some of these images.

I neglected to add tail to all my examples but it can easily be added/removed.

As prodigy Saiyan warrior she is able to achieve even more forms with just a little prompting!

You can change her hair color by simply specifying it.

Here are some example hair colors. Super Saiyan 5 lets goooo! lol

I'm running out of space to describe this model. I'll put the training data in the "About this version" section.


V3 Update (10/26/2023): V3 is trained with a new dataset that incudes interesting poses and different outfits. Overall it is more stable but the art style might be a little too strong?

Caulifla is easily my favorite character in Dragon Ball so I'll keep making updates if I can find good images.

I'll add in a Super Saiyan Caulifla once the base form is good.


Last few images are prototyping my Saiyan_Armor_DB Lora. I'll upload it once its finalized.



Weight: 0.7
Trigger: Caulifla_DB <-- Same as the Lora file name, isn't that easy to remember?
Extra prompts: bare shoulders, midriff,
Trained on 33 images

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데이터 없음
C
모델과 대화하기
공고
2024-11-03
모델 게시
2023-11-28
모델 정보 업데이트
모델 상세정보
유형
LORA
게시 날짜
2023-11-28
기본 모델
SDXL 1.0
트리거 단어
Super_Saiyan_4_Caulifla, 1girl, (crop top:1), long black hair, body fur, red fur
복사
버전 소개

[sdxl_arguments]

cache_text_encoder_outputs = false

no_half_vae = true

min_timestep = 0

max_timestep = 1000

shuffle_caption = true

lowram = true

[model_arguments]

pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"

vae = "/content/vae/sdxl_vae.safetensors"

[dataset_arguments]

debug_dataset = false

in_json = "/content/LoRA/meta_lat.json"

train_data_dir = "/content/drive/MyDrive/lora_training/datasets/Super_Saiyan_4_Caulifla_SDXL"

dataset_repeats = 10

keep_tokens = 1

resolution = "1024,1024"

color_aug = false

token_warmup_min = 1

token_warmup_step = 0

[training_arguments]

output_dir = "/content/drive/MyDrive/kohya-trainer/output/Super_Saiyan_4_Caulifla_SDXL"

output_name = "Super_Saiyan_4_Caulifla_SDXL"

save_precision = "fp16"

save_every_n_epochs = 1

train_batch_size = 4

max_token_length = 225

mem_eff_attn = false

sdpa = true

xformers = false

max_train_epochs = 10

max_data_loader_n_workers = 8

persistent_data_loader_workers = true

gradient_checkpointing = true

gradient_accumulation_steps = 1

mixed_precision = "fp16"

[logging_arguments]

log_with = "tensorboard"

logging_dir = "/content/LoRA/logs"

log_prefix = "Super_Saiyan_4_Caulifla_SDXL"

[sample_prompt_arguments]

sample_sampler = "euler_a"

[saving_arguments]

save_model_as = "safetensors"

[optimizer_arguments]

optimizer_type = "AdaFactor"

learning_rate = 0.0001

max_grad_norm = 0

optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False",]

lr_scheduler = "constant_with_warmup"

lr_warmup_steps = 100

[additional_network_arguments]

no_metadata = false

network_module = "networks.lora"

network_dim = 64

network_alpha = 32

network_args = []

network_train_unet_only = true

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