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---
language:
- en
pipeline_tag: text-to-image
library_name: diffusers
tags:
- text-to-image
- stable-diffusion
- safetensors
- stable-diffusion-xl
- merge
license: openrail++
base_model:
- cagliostrolab/animagine-xl-3.1
- Eugeoter/anime_illust_diffusion_xl
- RunDiffusion/Juggernaut-XL-v9
- KBlueLeaf/Kohaku-XL-Zeta
- votepurchase/Starry-XL-v5.2
- cagliostrolab/animagine-xl-4.0
- kayfahaarukku/UrangDiffusion-2.0
- Raelina/Rae-Diffusion-XL-V2
- yodayo-ai/clandestine-xl-1.0
---
<style>
.container {
display: flex;
gap: 2rem;
align-items: flex-start;
}
.image-wrapper,
.details {
flex: 1 1 50%;
}
.image-wrapper {
display: flex;
justify-content: center;
align-items: center;
}
.model-image {
width: 100%;
max-width: 500px;
min-width: 300px;
border-radius: 8px;
box-shadow: 0 8px 20px rgba(0, 0, 0, 0.3);
}
.details h1 {
margin-top: 0;
font-size: 2rem;
color: #fff;
}
.details .description {
margin: 0.5rem 0 1.5rem;
line-height: 1.5;
color: #ccc;
}
.features-list {
list-style: none;
padding: 0;
margin: 0 0 1.5rem;
}
.features-list li {
display: flex;
align-items: center;
margin-bottom: 0.5rem;
font-size: 1rem;
color: #fff;
}
.features-list .icon {
margin-right: 0.6rem;
font-size: 1.2rem;
}
.badge-list {
list-style: none;
padding: 0;
margin: 0;
display: flex;
flex-wrap: wrap;
row-gap: 0.25rem;
column-gap: 0.5rem;
}
.badge-list li {
margin: 0;
}
.badge-btn {
display: inline-flex;
align-items: center;
height: 28px;
padding: 0 10px;
font-size: 14px;
font-weight: 500;
color: #fff;
text-decoration: none;
border-radius: 4px;
white-space: nowrap;
transition: opacity 0.2s, transform 0.1s;
}
.badge-btn .btn-icon {
width: 16px;
height: 16px;
margin-right: 6px;
}
.badge-btn:hover {
opacity: 0.85;
transform: translateY(-1px);
}
.badge-btn.civitai {
background-color: #2975fa8d;
}
.badge-btn.hf {
background-color: #ff66008d;
}
@media (max-width: 700px) {
.container {
flex-direction: column;
align-items: center;
}
.image-wrapper,
.details {
flex: unset;
width: 100%;
}
.model-image {
width: 90%;
max-width: 500px;
min-width: auto;
margin-bottom: 1rem;
}
}
</style>
<div class="container">
<div class="image-wrapper">
<img
src="https://huggingface.co/rityak/animagus/resolve/main/img.png"
alt="Animagus XL 1.0 Example"
class="model-image"
/>
</div>
<div class="details">
<h1>Animagus XL 1.0</h1>
<p class="description">
<strong>Animagus</strong> is an anime-themed finetuned model built on top of Stable Diffusion XL, created as part of the Animagine XL series. The model merges multiple specialized checkpoints using advanced multistage methods (<code>karcher_mean</code>, <code>ties_sum</code> and <code>task_arithmetic</code>) and is then fine-tuned on carefully selected illustration datasets. This process delivers more stable outputs, accurate anatomy, and rich colors, while preserving the “anime” style.
</p>
<ul class="badge-list">
<li>
<a
href="https://civitai.com/models/1783095"
target="_blank"
class="badge-btn civitai"
>
<img
src="https://civitai.com/favicon-blue.ico"
alt="CivitAI"
class="btn-icon"
/>
View on CivitAI
</a>
</li>
<li>
<a
href="https://huggingface.co/rityak/animagus/resolve/main/animagus.safetensors?download=true"
target="_blank"
class="badge-btn hf"
>
<img
src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg"
alt="Hugging Face"
class="btn-icon"
/>
Download Animagus XL 1.0
</a>
</li>
<li>
<a
href="https://huggingface.co/rityak/animagus/resolve/main/animagus-zero.safetensors?download=true"
target="_blank"
class="badge-btn hf"
>
<img
src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg"
alt="Hugging Face"
class="btn-icon"
/>
Download Animagus XL Zero
</a>
</li>
</ul>
</div>
</div>
- **Civitai hub**
Explore model details, community examples, and usage tips:
[View on CivitAI](https://civitai.com/models/1783095)
- **Animagus XL 1.0 (fine‑tuned)**
The final anime‑optimized model _after_ fine‑tuning on curated illustration datasets.
[Download Animagus XL 1.0](https://huggingface.co/rityak/animagus/resolve/main/animagus.safetensors?download=true)
- **Animagus XL Zero (raw merge)**
A direct merge of all source checkpoints _before_ fine‑tuning.
[Download Animagus XL Zero](https://huggingface.co/rityak/animagus/resolve/main/animagus-zero.safetensors?download=true)
## Model Details
- **Model type**: diffusion-based text-to-image
- **Base checkpoint**: Stable Diffusion XL 1.0
- **Initial finetuned models**: Animagine XL 3.1 and Animagine XL 4.0 Opt
- **License**: CreativeML Open RAIL++-M
## Training Pipeline
**Step 1: Model Merging**
Multistage merging of over 20 anime-specific checkpoints using the following methods:
- **Karcher mean** (Riemannian center of mass): a generalization of the arithmetic mean to curved spaces (Riemannian manifolds), finding the point that minimizes the sum of squared Riemannian distances to all checkpoints.
- **subtract** and **add_difference** to preserve the unique characteristics of each checkpoint
- **fallback** and **task_arithmetic** for flexible combination of UNet, VAE, and CLIP components
**Step 2: Fine-tuning**
A few short iterations on a small but high-quality dataset:
- **pixiv** – a collection of illustrations with high aesthetic scores
- **latum** – expressive artworks with pleasant tones and fine line work
- **artists** – artworks by `asou`, `hara_harayutaka`, `hiroki_yyqw7151` in a vanilla anime screencap style
- **aiga** – AI-generated images with high aesthetic scores
- **anime** – screenshots and illustrations from anime and hentai
> **Note:** UNet and CLIP were fine-tuned separately due to an initial configuration error.
## Styles Reference
You can influence the visual style of generated images by including artist or style tags in your prompt. For a curated list of artist tags that have been tested with Animagus (compiled from the various checkpoints used in the merge), download the reference here:
**Download artist list**:
https://huggingface.co/rityak/animagus/raw/main/artist_list.txt
> **Note:** This list was gathered from models used during merging and serves as a helpful starting point, but not all tags are guaranteed to work equally well. Feel free to experiment and discover which styles best suit your use case.
## Usage Guidelines
The usage guidelines will be the same as for Animagine 3.1 and 4.0. For more details, please refer to:
- https://huggingface.co/cagliostrolab/animagine-xl-4.0
- https://huggingface.co/cagliostrolab/animagine-xl-3.1
---
### Recipe
**Step 1. Merging** **[Animagus XL Zero](https://huggingface.co/rityak/animagus/resolve/main/animagus-zero.safetensors?download=true)** - Non-trained merging of checkpoints.
```yaml
version: 0.1.0
model "SDXL\animagine\animagine-xl-4.0-opt.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\animagine\animagine-xl-3.1.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\babesByStableYogiSDXL_v50FP16.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\bigasp_v20.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\juggernautXL_ragnarokBy.safetensors" model_config="sdxl-sgm" merge_space="weight"
merge "karcher_mean_with_blocks" &2 &3 &4 alpha_clip_l=null alpha_clip_g=null alpha_in=null alpha_mid=null alpha_out=null alpha_embed_time=null alpha_embed_label=null max_iter=30.000000000000007 tol="3e-08" alpha_global="0.4, 0.3, 0.3"
merge "merge_checkpointing" &5
model "SDXL\sd_xl_base_1.0.safetensors" model_config="sdxl-sgm" merge_space="weight"
merge "subtract" &6 &7
literal 0.0 model_config="sdxl-sgm" merge_space="param"
merge "pick_component" &9 "clip_l"
merge "pick_component" &9 "clip_g"
merge "fallback" &10 &11
merge "pick_component" &9 "vae"
merge "fallback" &12 &13
literal 1.0000000000000002 model_config="sdxl-sgm" merge_space="param"
merge "pick_component" &15 "diffuser"
merge "fallback" &14 &16
merge "add_difference" &1 &8 &17
merge "fallback" &18 &1
model "SDXL\tofuANIMEBASEMODEL_050.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\kohakuXLZeta_rev1.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\starryXLV52_v52.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\hassakuXL_betaV06.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\animeIllustDiffusion_v08.safetensors" model_config="sdxl-sgm" merge_space="weight"
merge "karcher_mean_with_blocks" &1 &20 &21 &22 &23 &24 alpha_clip_l=null alpha_clip_g=null alpha_in=null alpha_mid=null alpha_out=null alpha_embed_time=null alpha_embed_label=null max_iter=30.000000000000007 tol="3e-08" alpha_global="0.1675, 0.1665, 0.1665, 0.1665, 0.1665, 0.1665"
merge "merge_checkpointing" &25
merge "subtract" &26 &1
merge "add_difference" &19 &27 1.0
merge "fallback" &28 &19
model "SDXL\animagine\RaeDiffusion-XL-v2.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\animagine\UrangDiffusion-2.0.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\animagine\clandestine-xl-1.0.safetensors" model_config="sdxl-sgm" merge_space="weight"
model "SDXL\animagine\ranimeXLBaseOnAnimagine_v10.safetensors" model_config="sdxl-sgm" merge_space="weight"
merge "task_arithmetic" &1 &30 &31 &32 &33 lambda_=1.0 weights="0.22, 0.26, 0.26, 0.26"
merge "merge_checkpointing" &34
merge "subtract" &30 &1
merge "subtract" &31 &1
merge "subtract" &32 &1
merge "subtract" &33 &1
merge "ties_sum_extended" &36 &37 &38 &39 k=0.20000000000000004 vote_sgn=true apply_stock=false apply_median=true cos_eps=1e-06 eps=1e-06 maxiter=100 ftol=1e-20
merge "add_difference" &35 &40 1.0
merge "fallback" &41 &35
merge "subtract" &42 &1
merge "add_difference" &29 &43 1.0
merge "fallback" &44 &29
merge "karcher_mean" &0 &45 max_iter=30.000000000000007 tol="1e-07" alphas="0.35, 0.65"
```
**Step 2. Fine-tuning** **[Animagus XL](https://huggingface.co/rityak/animagus/resolve/main/animagus.safetensors?download=true)** A few short iterations on a small, high-quality dataset. |