New version is out: https://civarchive.com/models/628865/sotediffusion-v2
Anime finetune of Würstchen V3.
This release is sponsored by fal.ai/grants
Trained on 6M images for 3 epochs using 8x A100 80G GPUs.
This model can be used via API with Fal.AI
For more details: https://fal.ai/models/fal-ai/stable-cascade/sote-diffusion
Please refer to Huggingface for SD.Next UI, Diffusers or UNet models:
https://huggingface.co/Disty0/sotediffusion-wuerstchen3
CivitAI page has only the ComfyUI checkpoint models.
Inference Parameters:
Download the Main model (8.14 GB file):
https://civarchive.com/api/download/models/563950?type=Model&format=SafeTensor&size=pruned&fp=fp16
Download the Decoder model (4.24 GB file):
https://civarchive.com/api/download/models/563892?type=Model&format=SafeTensor&size=pruned&fp=fp16
Positives:
newest, extremely aesthetic, best quality,Negatives:
very displeasing, worst quality, monochrome, realistic, oldest, loli,Main:
Sampler: DDPM or DPMPP 2M with SGM Uniform
CFG: 7
Steps: 30 or 40
Decoder:
Sampler: Euler a Karras
CFG: 1 or 1.2
Steps: 10
Compression: 42 (or 32 to 64)
Resolution: 1024x1536, 2048x1152.
Anything works as long as it's a multiply of 128.
Training:
Software used: Kohya SD-Scripts with Stable Cascade branch.
https://github.com/kohya-ss/sd-scripts/tree/stable-cascade
GPU used: 8x Nvidia A100 80GB
GPU hours: 220
Base
parameters | value
amp | bf16
weights | fp32
save weights | fp16
resolution | 1024x1024
effective batch size | 128
unet learning rate | 1e-5
te learning rate | 4e-6
optimizer | Adafactor
images | 6M
epochs | 3
Final
parameters | value
amp | bf16
weights | fp32
save weights | fp16
resolution | 1024x1024
effective batch size | 128
unet learning rate | 4e-6
te learning rate | none
optimizer | Adafactor
images | 120K
epochs | 16
Dataset:
GPU used for captioning: 1x Intel ARC A770 16GB
GPU hours: 350
Model used for captioning: SmilingWolf/wd-swinv2-tagger-v3
Model used for text: llava-hf/llava-1.5-7b-hf
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
newest : 1.85M
recent : 1.38M
mid : 993K
early : 566K
oldest : 160K
pixiv : 344K
visual novel cg : 231K
anime wallpaper : 105K
Total: 5.628.499 images
Note:
Smallest size is 1280x600 / 768.000 pixels
Deduped based on image similarity using czkawka-cli
Around 120K very high quality images got intentionally duplicated 5 times, making the total image count 6.2M
Tags:
Tag Format:
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 tagsDate:
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-2
score > 0.90 : extremely aesthetic
score > 0.80 : very aesthetic
score > 0.70 : aesthetic
score > 0.50 : slightly aesthetic
score > 0.40 : not displeasing
score > 0.30 : not aesthetic
score > 0.25 : slightly displeasing
score > 0.10 : displeasing
rest of them : very displeasing
Quality Tags:
Model used: https://huggingface.co/hakurei/waifu-diffusion-v1-4/blob/main/models/aes-B32-v0.pth
score > 0.980 : best quality
score > 0.900 : high quality
score > 0.750 : great quality
score > 0.500 : medium quality
score > 0.250 : normal quality
score > 0.125 : bad quality
score > 0.025 : low quality
rest of them : worst quality
Rating Tags:
general
sensitive
nsfw
explicit nsfw
Custom Tags:
image boards: date,
text: The text says "text",
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,
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.
Description
This is the Stage B / Decoder
Trained on 98K images that got more than 0.98 score on both quality and aesthetic taggers from the newest dataset.
FAQ
Comments (4)
It doesn't work :(
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(Update) Summary: Automatic1111 does not support Stable Cascade
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I say "it doesn't work" because the images don't come out as expected from the model.
They appear realistic, rather than anime-style.
I'll post a simple image for you to see the result.
I just added the model and tried it on.
Since it came out with a realistic image, I tried the test image prompt (the girl with the red hair)
And yet it still showed realistic images.
Maybe a specific tag is needed? But since I've used the positive prompt, there shouldn't be a problem... :/
(Edit)
I see the example images, next to Seed, CFG scale, Sampler.... they also have "Workflow 12 nodes"
Maybe you need to use workflow to make it work?
I really have no idea, but I love how the model looks
+Info
I attach the following information in case it is of any use to you
version: 1.5.2 • python: 3.10.6 • torch: 2.0.1+cu118 • xformers: 0.0.20 • gradio: 3.32.0 • checkpoint: 1f5f4977dc
Like i said in the model description, it can still fall back to realistic. Add "anime illustration" tag when this happens.
But you shouldn't get a different results with the sample images, did you download the Stage C?
Looking at your sample images, you've downloaded the Stage B. That's not the actual model. Stage B is the decoder for Stage C. Stage C is the actual model.
And how are you able to run Stable Cascade on A1111?
If you are using that Stable Cascade extension, you can't use this model with it.
Only UIs capable of running Stable Cascade are ComfyUI and SD.Next.
@Disty0 It doesn't seem to work.
With "anime illustration" comes a real girl with an anime shirt XD
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Models:
I first downloaded the C version and used it like any other model.
Windows 10: Models Folder
And load the model
At least all the downloaded models work for me.
Note: The only models that don't work for me are the XL because I'm using an older version.
I use an older version because when I updated I couldn't find "Extra Networks" and I didn't have time to figure out how everything worked again :/
But the non-XL models work perfectly for me... at least around 30 different models.
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Stable Cascade
Okay, then that's why.
Use Stable Diffusion with Automatic1111.
Thanks for the help.
For now I'll save the url for a future.
And I'll remove the test images that I've uploaded so they don't give the wrong impression.
Details
Available On (1 platform)
Same model published on other platforms. May have additional downloads or version variants.