Initial v1 version.
Depending on the artist prompted you may want to include the following prompt but it's not necessary.
Positive: colored lineart
Negative: blending, no lineart



This is more of an as-is model that I created with two images in 60 steps on ΣΙΗ 1.5 so I am not promising that it is well made.
Made using: TrainTrain
Dataset: Left as Origin and right as Target
The differences are subtle because even small isolated differences have a large impact and this method is less destructive when resizing.
TrainTrain .json settings: Truncated based on what I changed from default.
{
"network_type": "lierla",
"network_rank": "4",
"network_alpha": "4",
"train_iterations": "60",
"train_batch_size": "1",
"train_learning_rate": "0.0001",
"train_optimizer": "AdamW",
"train_lr_scheduler": "cosine_annealing",
"train_lr_scheduler_settings": "eta_min=0.00002",
"use_gradient_checkpointing": true,
"network_blocks(BASE = TextEncoder)": [
"IN00", "IN01", "IN02", "IN03", "IN04", "IN05", "IN06", "IN07", "IN08", "IN09", "IN10", "IN11", "M00", "OUT00", "OUT02", "OUT03", "OUT04", "OUT06", "OUT07", "OUT08", "OUT09", "OUT10", "OUT11", "OUT05", "OUT01"
],
"network_strength": "1.0",
"network_conv_rank": "0",
"network_conv_alpha": "0",
"network_element": "Full",
"network_train_text_encoder": false,
"image_max_ratio": "2.0",
"train_min_timesteps": "400",
"train_max_timesteps": "800",
"train_loss_function": "Smooth-L1",
"train_lr_scheduler_num_cycles": "1",
"train_lr_scheduler_power": "1.0",
"train_snr_gamma": "1.0",
"diff_alt_ratio": "1.0",
"diff_revert_original_target": true,
"diff_use_diff_mask": false,
"model_v_pred": true,
"mode": "ADDifT",
}
Model Trimming: After various block weight xyz tests I used Supermerger to alter the model to :1.3:OUTALL 1.3 weight because I was using :2 in tests but the supermerger process would essentially triple the saved model weight if I kept it at 2.
Initial v1 version.
Depending on the artist prompted you may want to include the following prompt but it's not necessary.
Positive: colored lineart
Negative: blending, no lineart
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