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sotediffusion-wuerstchen3-alpha3

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metadata
pipeline_tag: text-to-image
license: other
license_name: faipl-1.0-sd
license_link: LICENSE
decoder:
  - Disty0/sotediffusion-wuerstchen3-alpha1-decoder

SoteDiffusion Wuerstchen3

Anime finetune of Würstchen V3.
Currently is in early state in training.
No commercial use.

Release Notes

  • Switched to OneTrainer
  • Trained more.
  • Currenty trained on 2,6M images.

UI Guide

SD.Next

URL: https://github.com/vladmandic/automatic/

Switch to the dev branch:

git checkout dev

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: 

very aesthetic, best quality, newest,

Negative Prompt: 

very displeasing, worst quality, oldest, monochrome, sketch, realistic,

Parameters:
Sampler: Default

Steps: 30 or 40
Refiner Steps: 10

CFG: 6-8
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

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, cowboy shot, straight hair, looking at viewer, hoodie, indoors, slight smile, casual, furniture, doorway, very aesthetic, best quality, newest,"
negative_prompt = "very displeasing, worst quality, oldest, monochrome, sketch, realistic,"

output = pipe(
    width=1024,
    height=1536,
    prompt=prompt,
    negative_prompt=negative_prompt,
    decoder_guidance_scale=1.0,
    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 done done
pixiv done done
visual novel cg done done
anime wallpaper done 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,
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:

  1. Modification Sharing: If you modify SoteDiffusion models, you must share both your changes and the original license.
  2. 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.
  3. Distribution Terms: Any distribution must be under this license or another with similar rules.
  4. 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.