Go to Models -> Huggingface and type Disty0/sotediffusion-wuerstchen3-alpha3-decoder into the model name and press download.
Load Disty0/sotediffusion-wuerstchen3-alpha3-decoder after the download process is complete.

Prompt:

extremely aesthetic, best quality, newest,

Negative Prompt:

very displeasing, worst quality, monochrome, sketch, realistic, oldest, visual novel cg,

Parameters:
Sampler: Default

Steps: 30 or 40
Refiner Steps: 10

CFG: 8-6
Secondary CFG: 2 or 1

Resolution: 1024x1536, 2048x1152
Anything works as long as it's a multiply of 128.

ComfyUI

Please refer to CivitAI: https://civitai.com/models/353284

Code Example

pip install diffusers

python

import torch
from diffusers import StableCascadeCombinedPipeline

device = "cuda"
dtype = torch.bfloat16 # or torch.float16
model = "Disty0/sotediffusion-wuerstchen3-alpha3-decoder"

pipe = StableCascadeCombinedPipeline.from_pretrained(model, torch_dtype=dtype)

# send everything to the gpu:
pipe = pipe.to(device, dtype=dtype)
pipe.prior_pipe = pipe.prior_pipe.to(device, dtype=dtype)

# or enable model offload to save vram:
# pipe.enable_model_cpu_offload()



prompt = "1girl, solo, cat ears, straight hair, pink hair, orange eyes, bare shoulders, looking at viewer, smile, newest, extremely aesthetic, best quality, general, black background, wind, petals, feathers, magic, electricity, bioluminescence, depth of field, fireflies, head tilt, fire, space,"
negative_prompt = "very displeasing, worst quality, monochrome, sketch, realistic, oldest, visual novel cg,"
output = pipe(
    width=1024,
    height=1536,
    prompt=prompt,
    negative_prompt=negative_prompt,
    decoder_guidance_scale=2.0,
    prior_guidance_scale=8.0,
    prior_num_inference_steps=40,
    output_type="pil",
    num_inference_steps=10
).images[0]

## do something with the output image

Training Status:

GPU used for training: 1x AMD RX 7900 XTX 24GB
GPU Hours: 500 (Accumulative starting from alpha1)

dataset name	training done	remaining
newest	100	131
recent	040	132
mid	040	084
early	040	030
oldest	020	done
pixiv	042	done
visual novel cg	028	done
anime wallpaper	013	done
Total	333	375

Note: chunks starts from 0 and there are 8000 images per chunk

Dataset:

GPU used for captioning: 1x Intel ARC A770 16GB
GPU Hours: 350

Model used for captioning: SmilingWolf/wd-swinv2-tagger-v3
Command:

python /mnt/DataSSD/AI/Apps/kohya_ss/sd-scripts/finetune/tag_images_by_wd14_tagger.py --model_dir "/mnt/DataSSD/AI/models/wd14_tagger_model" --repo_id "SmilingWolf/wd-swinv2-tagger-v3" --recursive --remove_underscore --use_rating_tags --character_tags_first --character_tag_expand --append_tags --onnx --caption_separator ", " --general_threshold 0.35 --character_threshold 0.50 --batch_size 4 --caption_extension ".txt" ./

dataset name	total images	total chunk
newest	1.848.331	232
recent	1.380.630	173
mid	993.227	125
early	566.152	071
oldest	160.397	021
pixiv	343.614	043
visual novel cg	231.358	029
anime wallpaper	104.790	014
Total	5.628.499	708

Note:

Smallest size is 1280x600 | 768.000 pixels
Deduped based on image similarity using czkawka-cli

Tags:

Model is trained with random tag order but this is the order in the dataset if you are interested:

aesthetic tags, quality tags, date tags, custom tags, rating tags, character, series, rest of the tags

Date:

tag	date
newest	2022 to 2024
recent	2019 to 2021
mid	2015 to 2018
early	2011 to 2014
oldest	2005 to 2010

Aesthetic Tags:

Model used: shadowlilac/aesthetic-shadow-v2

score greater than	tag	count
0.90	extremely aesthetic	125.451
0.80	very aesthetic	887.382
0.70	aesthetic	1.049.857
0.50	slightly aesthetic	1.643.091
0.40	not displeasing	569.543
0.30	not aesthetic	445.188
0.20	slightly displeasing	341.424
0.10	displeasing	237.660
rest of them	very displeasing	328.712

Quality Tags:

Model used: https://huggingface.co/hakurei/waifu-diffusion-v1-4/blob/main/models/aes-B32-v0.pth

score greater than	tag	count
0.980	best quality	1.270.447
0.900	high quality	498.244
0.750	great quality	351.006
0.500	medium quality	366.448
0.250	normal quality	368.380
0.125	bad quality	279.050
0.025	low quality	538.958
rest of them	worst quality	1.955.966

Rating Tags

tag	count
general	1.416.451
sensitive	3.447.664
nsfw	427.459
explicit nsfw	336.925

Custom Tags:

dataset name	custom tag
image boards	date,
characters	character, series
pixiv	art by Display_Name,
visual novel cg	Full_VN_Name (short_3_letter_name), visual novel cg,
anime wallpaper	date, anime wallpaper,

Training Parameters:

Software used: OneTrainer
https://github.com/Nerogar/OneTrainer/

Base model: Disty0/sote-diffusion-cascade-alpha2

Config:

{
    "__version": 3,
    "training_method": "FINE_TUNE",
    "model_type": "STABLE_CASCADE_1",
    "debug_mode": false,
    "debug_dir": "debug",
    "workspace_dir": "/mnt/DataSSD/AI/SoteDiffusion/Wuerstchen3/OneTrainer/run",
    "cache_dir": "/mnt/DataSSD/AI/SoteDiffusion/Wuerstchen3/OneTrainer/workspace-cache/run",
    "tensorboard": true,
    "tensorboard_expose": false,
    "continue_last_backup": true,
    "include_train_config": "NONE",
    "base_model_name": "Disty0/sotediffusion-wuerstchen3-alpha2",
    "weight_dtype": "BFLOAT_16",
    "output_dtype": "BFLOAT_16",
    "output_model_format": "SAFETENSORS",
    "output_model_destination": "/mnt/DataSSD/AI/SoteDiffusion/Wuerstchen3/OneTrainer/workspace-cache/models",
    "gradient_checkpointing": true,
    "force_circular_padding": false,
    "concept_file_name": "training_concepts/concepts.json",
    "concepts": [
        {
            "__version": 1,
            "image": {
                "__version": 0,
                "enable_crop_jitter": false,
                "enable_random_flip": false,
                "enable_fixed_flip": false,
                "enable_random_rotate": false,
                "enable_fixed_rotate": false,
                "random_rotate_max_angle": 0.0,
                "enable_random_brightness": false,
                "enable_fixed_brightness": false,
                "random_brightness_max_strength": 0.0,
                "enable_random_contrast": false,
                "enable_fixed_contrast": false,
                "random_contrast_max_strength": 0.0,
                "enable_random_saturation": false,
                "enable_fixed_saturation": false,
                "random_saturation_max_strength": 0.0,
                "enable_random_hue": false,
                "enable_fixed_hue": false,
                "random_hue_max_strength": 0.0,
                "enable_resolution_override": false,
                "resolution_override": "1024"
            },
            "text": {
                "__version": 0,
                "prompt_source": "sample",
                "prompt_path": "",
                "enable_tag_shuffling": true,
                "tag_delimiter": ", ",
                "keep_tags_count": 1
            },
            "name": "",
            "path": "/mnt/DataSSD/AI/anime_image_dataset/best/newest_best",
            "seed": -209204630,
            "enabled": true,
            "include_subdirectories": true,
            "image_variations": 1,
            "text_variations": 1,
            "balancing": 1.0,
            "balancing_strategy": "REPEATS",
            "loss_weight": 1.0
        }
    ],
    "circular_mask_generation": false,
    "random_rotate_and_crop": false,
    "aspect_ratio_bucketing": true,
    "latent_caching": true,
    "clear_cache_before_training": false,
    "learning_rate_scheduler": "CONSTANT",
    "learning_rate": 1e-05,
    "learning_rate_warmup_steps": 200,
    "learning_rate_cycles": 1,
    "epochs": 1,
    "batch_size": 16,
    "gradient_accumulation_steps": 1,
    "ema": "OFF",
    "ema_decay": 0.999,
    "ema_update_step_interval": 5,
    "dataloader_threads": 8,
    "train_device": "cuda",
    "temp_device": "cpu",
    "train_dtype": "FLOAT_16",
    "fallback_train_dtype": "BFLOAT_16",
    "enable_autocast_cache": true,
    "only_cache": false,
    "resolution": "1024",
    "attention_mechanism": "SDP",
    "align_prop": false,
    "align_prop_probability": 0.1,
    "align_prop_loss": "AESTHETIC",
    "align_prop_weight": 0.01,
    "align_prop_steps": 20,
    "align_prop_truncate_steps": 0.5,
    "align_prop_cfg_scale": 7.0,
    "mse_strength": 1.0,
    "mae_strength": 0.0,
    "vb_loss_strength": 1.0,
    "loss_weight_fn": "P2",
    "loss_weight_strength": 1.0,
    "dropout_probability": 0.0,
    "loss_scaler": "NONE",
    "learning_rate_scaler": "NONE",
    "offset_noise_weight": 0.0,
    "perturbation_noise_weight": 0.0,
    "rescale_noise_scheduler_to_zero_terminal_snr": false,
    "force_v_prediction": false,
    "force_epsilon_prediction": false,
    "min_noising_strength": 0.0,
    "max_noising_strength": 1.0,
    "noising_weight": 0.0,
    "noising_bias": 0.5,
    "unet": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": 0,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "NONE"
    },
    "prior": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": 0,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "NONE"
    },
    "text_encoder": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": 0,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "NONE"
    },
    "text_encoder_layer_skip": 0,
    "text_encoder_2": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": 30,
        "stop_training_after_unit": "EPOCH",
        "learning_rate": null,
        "weight_dtype": "NONE"
    },
    "text_encoder_2_layer_skip": 0,
    "vae": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": null,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "FLOAT_32"
    },
    "effnet_encoder": {
        "__version": 0,
        "model_name": "/mnt/DataSSD/AI/models/wuerstchen3/effnet_encoder.safetensors",
        "train": true,
        "stop_training_after": null,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "FLOAT_16"
    },
    "decoder": {
        "__version": 0,
        "model_name": "Disty0/sotediffusion-wuerstchen3-alpha2-decoder",
        "train": true,
        "stop_training_after": null,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "FLOAT_16"
    },
    "decoder_text_encoder": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": null,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "NONE"
    },
    "decoder_vqgan": {
        "__version": 0,
        "model_name": "",
        "train": true,
        "stop_training_after": null,
        "stop_training_after_unit": "NEVER",
        "learning_rate": null,
        "weight_dtype": "FLOAT_16"
    },
    "masked_training": false,
    "unmasked_probability": 0.1,
    "unmasked_weight": 0.1,
    "normalize_masked_area_loss": false,
    "embedding_learning_rate": null,
    "preserve_embedding_norm": false,
    "embedding": {
        "__version": 0,
        "uuid": "bf3a36b4-bd01-4b46-b818-3c6414887497",
        "model_name": "",
        "placeholder": "<embedding>",
        "train": true,
        "stop_training_after": null,
        "stop_training_after_unit": "NEVER",
        "token_count": 1,
        "initial_embedding_text": "*"
    },
    "additional_embeddings": [],
    "embedding_weight_dtype": "FLOAT_32",
    "lora_model_name": "",
    "lora_rank": 16,
    "lora_alpha": 1.0,
    "lora_weight_dtype": "FLOAT_32",
    "optimizer": {
        "__version": 0,
        "optimizer": "ADAFACTOR",
        "adam_w_mode": false,
        "alpha": null,
        "amsgrad": false,
        "beta1": null,
        "beta2": null,
        "beta3": null,
        "bias_correction": false,
        "block_wise": false,
        "capturable": false,
        "centered": false,
        "clip_threshold": 1.0,
        "d0": null,
        "d_coef": null,
        "dampening": null,
        "decay_rate": -0.8,
        "decouple": false,
        "differentiable": false,
        "eps": 1e-30,
        "eps2": 0.001,
        "foreach": false,
        "fsdp_in_use": false,
        "fused": false,
        "fused_back_pass": true,
        "growth_rate": null,
        "initial_accumulator_value": null,
        "is_paged": false,
        "log_every": null,
        "lr_decay": null,
        "max_unorm": null,
        "maximize": false,
        "min_8bit_size": null,
        "momentum": null,
        "nesterov": false,
        "no_prox": false,
        "optim_bits": null,
        "percentile_clipping": null,
        "r": null,
        "relative_step": false,
        "safeguard_warmup": false,
        "scale_parameter": false,
        "stochastic_rounding": true,
        "use_bias_correction": false,
        "use_triton": false,
        "warmup_init": false,
        "weight_decay": 0.0,
        "weight_lr_power": null
    },
    "optimizer_defaults": {
        "ADAFACTOR": {
            "__version": 0,
            "optimizer": "ADAFACTOR",
            "adam_w_mode": false,
            "alpha": null,
            "amsgrad": false,
            "beta1": null,
            "beta2": null,
            "beta3": null,
            "bias_correction": false,
            "block_wise": false,
            "capturable": false,
            "centered": false,
            "clip_threshold": 1.0,
            "d0": null,
            "d_coef": null,
            "dampening": null,
            "decay_rate": -0.8,
            "decouple": false,
            "differentiable": false,
            "eps": 1e-30,
            "eps2": 0.001,
            "foreach": false,
            "fsdp_in_use": false,
            "fused": false,
            "fused_back_pass": true,
            "growth_rate": null,
            "initial_accumulator_value": null,
            "is_paged": false,
            "log_every": null,
            "lr_decay": null,
            "max_unorm": null,
            "maximize": false,
            "min_8bit_size": null,
            "momentum": null,
            "nesterov": false,
            "no_prox": false,
            "optim_bits": null,
            "percentile_clipping": null,
            "r": null,
            "relative_step": false,
            "safeguard_warmup": false,
            "scale_parameter": false,
            "stochastic_rounding": true,
            "use_bias_correction": false,
            "use_triton": false,
            "warmup_init": false,
            "weight_decay": 0.0,
            "weight_lr_power": null
        }
    },
    "sample_definition_file_name": "training_samples/samples.json",
    "samples": [
        {
            "__version": 0,
            "enabled": true,
            "prompt": "very aesthetic, best quality, newest, sensitive, 1girl, solo, upper body,",
            "negative_prompt": "monochrome, sketch, fat,",
            "height": 1024,
            "width": 1024,
            "seed": 42,
            "random_seed": true,
            "diffusion_steps": 30,
            "cfg_scale": 7.0,
            "noise_scheduler": "EULER_A"
        }
    ],
    "sample_after": 30,
    "sample_after_unit": "MINUTE",
    "sample_image_format": "JPG",
    "samples_to_tensorboard": true,
    "non_ema_sampling": true,
    "backup_after": 30,
    "backup_after_unit": "MINUTE",
    "rolling_backup": true,
    "rolling_backup_count": 10,
    "backup_before_save": true,
    "save_after": 30,
    "save_after_unit": "MINUTE",
    "save_filename_prefix": ""
}

Limitations and Bias

Bias

This model is intended for anime illustrations.
Realistic capabilites are not tested at all.

Limitations

Can fall back to realistic.
Add "realistic" tag to the negatives when this happens.
Far shot eyes can be bad.
Anatomy and hands can be bad.
Still in active training.

License

SoteDiffusion models falls under Fair AI Public License 1.0-SD license, which is compatible with Stable Diffusion models’ license. Key points:

Modification Sharing: If you modify SoteDiffusion models, you must share both your changes and the original license.
Source Code Accessibility: If your modified version is network-accessible, provide a way (like a download link) for others to get the source code. This applies to derived models too.
Distribution Terms: Any distribution must be under this license or another with similar rules.
Compliance: Non-compliance must be fixed within 30 days to avoid license termination, emphasizing transparency and adherence to open-source values.

Notes: Anything not covered by Fair AI license is inherited from Stability AI Non-Commercial license which is named as LICENSE_INHERIT. Meaning, still no commercial use of any kind.