Anima V1
Trained base on Anima V0.1 base with LoRA_Easy_Training_Scripts. See about this version for training details.
Chenkin Rectified-Flow V1
Trained base on Chenkin Rectified-Flow 0.3 with LoRA_Easy_Training_Scripts. See about this version for training details.
NOOB V-PRED V4
Trained based on NOOB V-PRED 1.0 with updated dataset and improved parameters.
NOOB V-PRED V3
Trained based on NOOB V-PRED 1.0 with Kohya SS. I switched to locon for smaller file size and better results. Setting min SNR = 3 and alpha = 1 improved the effectiveness of training. However it leads to more limb distortation. But I think it's acceptable when achieving better results in style generation.
See about the version for training details.
NOOB V-PRED V3
Trained based on NOOB V-PRED 1.0 with Kohya SS. I switched to locon for smaller file size and better results. Setting min SNR = 3 and alpha = 1 improved the effectiveness of training. However it leads to more limb distortation. But I think it's acceptable when achieving better results in style generation.
See about the version for training details.
NOOB V-PRED V2
Trained based on NOOB V-PRED 1.0 with OneTrainer. Better in color and lora adapation. See about the version for training details.
NOOB V-PRED V1
Trained based on NOOB V-PRED 0.65S. Recommend using it with V-PRED models.
No trigger word set in this version.
Introduction
A LyCORIS to generate the style of AI artist mirham. Setting the artist name "mirham" as the trigger word during training, but not recommending its use, can cause over baking. Just use the trigger word when you feel necessary, eg. using together with other lora or being suppressed by other styles.
Training details
See about the version.
Description
[[subsets]]
name = "5"
image_dir = "G:/dataset/style/mirham/5_mirham"
num_repeats = 5
shuffle_caption = true
caption_extension = ".txt"
random_crop_padding_percent = 0.05
caption_dropout_rate = 0.1
caption_tag_dropout_rate = 0.1
[train_mode]
train_mode = "lora"
[general_args.args]
persistent_data_loader_workers = true
vae_batch_size = 5
pretrained_model_name_or_path = ""
mixed_precision = "bf16"
gradient_checkpointing = true
gradient_accumulation_steps = 1
seed = 42
max_data_loader_n_workers = 1
max_token_length = 225
prior_loss_weight = 1.0
sdpa = true
max_train_epochs = 25
cache_latents = true
cache_latents_to_disk = true
[general_args.dataset_args]
resolution = 1024
batch_size = 1
[network_args.args]
network_dim = 64
network_alpha = 1.0
min_timestep = 0
max_timestep = 1000
network_train_unet_only = true
[optimizer_args.args]
optimizer_type = "ProdigyPlusScheduleFree"
lr_scheduler = "constant"
loss_type = "l2"
learning_rate = 1.0
unet_lr = 1.0
max_grad_norm = 1.0
min_snr_gamma = 1.0
[saving_args.args]
output_dir = "G:/LoRA_Easy_Training_Scripts/output"
output_name = "mirham-anima1.0-V1-locon-dim64conv16alpha0.01-SNR1"
save_precision = "bf16"
save_model_as = "safetensors"
save_every_n_epochs = 1
save_toml = true
save_toml_location = "G:/LoRA_Easy_Training_Scripts/output"
[sample_args.args]
sample_sampler = "euler"
sample_every_n_epochs = 1
sample_prompts = "G:/LoRA_Easy_Training_Scripts/anima sample.txt"
[logging_args.args]
log_prefix_mode = "disabled"
run_name_mode = "default"
[anima_args.args]
pretrained_model_name_or_path = "G:/sd-webui-forge-neo/models/Stable-diffusion/anima_baseV10.safetensors"
qwen3 = "G:/sd-webui-forge-neo/models/text_encoder/qwen_3_06b_base.safetensors"
vae = "G:/sd-webui-forge-neo/models/VAE/qwen_image_vae.safetensors"
qwen3_max_token_length = 512
t5_max_token_length = 512
timestep_sampling = "sigmoid"
sigmoid_scale = 1.0
discrete_flow_shift = 3.0
[edm_loss_args.args]
edm2_loss_weighting = false
[bucket_args.dataset_args]
enable_bucket = true
min_bucket_reso = 256
max_bucket_reso = 2048
bucket_reso_steps = 64
[network_args.args.network_args]
conv_dim = 16
conv_alpha = 1.0
train_llm_adapter = "False"
[optimizer_args.args.optimizer_args]
betas = "0.9,0.99"
beta3 = "None"
weight_decay = "0"
weight_decay_by_lr = "True"
d0 = "1e-6"
d_coef = "2"
d_limiter = "True"
prodigy_steps = "0"
schedulefree_c = "0"
eps = "1e-8"
split_groups = "True"
split_groups_mean = "False"
factored = "True"
factored_fp32 = "True"
use_bias_correction = "True"
use_stableadamw = "True"
use_schedulefree = "True"
use_speed = "False"
stochastic_rounding = "True"
fused_back_pass = "False"
use_cautious = "False"
use_grams = "False"
use_adopt = "False"
use_orthograd = "False"
use_focus = "False"