--- license: openrail++ datasets: - OnomaAIResearch/s1k_Korean - cagliostrolab/1.2m-ordered-tags-json language: - en base_model: - OnomaAIResearch/Illustrious-XL-v0.1 - OnomaAIResearch/Illustrious-XL-v2.0 - NeverWinter13/ars-divina-7.2.4a - NeverWinter13/indominus-rex-xl tags: - text-to-image - stable-diffusion-xl - sdxl - illustrious - merge-train - cyclical-training - anime - illustration inference: true --- # Aeterna Opus **Overview** **Aeterna Opus** is a 'premium', high-fidelity anime-themed text-to-image generative model and the latest installment in the series. Built on a structurally sound custom foundation, the model bridges the gap between painterly artistic depth and rigorous character alignment frameworks. The underlying backbone merges the atmospheric lighting of Ars Divina 7.2.4a with the anatomical precision of Indominus Rex XL. Rather than relying on standard fine-tuning, the merged weights underwent continuous, multi-epoch cyclical re-training, constantly rotating optimization passes between OnomaAI’s s1k_Korean dataset for natural language layout logic and CagliostroLab’s 1.2M Ordered Tags for strict Danbooru token compliance. These enhancements make Aeterna Opus highly adaptive, delivering exceptional structural stability and dual-format prompt adherence while maintaining a signature, illustrative edge. ## 🧬 Architectural & Training Pipeline Rather than relying on basic fine-tuning, Aeterna Opus utilizes a complex structural and aesthetic convergence process: 1. **The Foundation (Merge Backbone):** The core weights are derived from a powerful merge of **Ars Divina 7.2.4a** (celebrated for the 'random bullshit go' merging process by yours truly; built originally from **Illustrious XL 0.1** and **Pony Diffusion v6**) and **Indominus Rex XL** (famed for anatomical precision and dynamic structural composition). 2. **The Cyclic Refinement (Re-training):** This merged backbone was subjected to continuous, alternating training iterations using **Illustrious-XL-v2.0** principles. The cyclical schedule continuously rotated optimization tasks between: * **OnomaAI s1k_Korean Dataset:** Embedding natural language prompt comprehension, unique stylistic variety, and robust high-resolution layout logic ($1536 \times 1536$ native capabilities). * **CagliostroLab 1.2M Ordered Tags:** Polishing fine-grain detailing, mitigating aesthetic artifacts, and ensuring strict Danbooru tag ordering and consistency. The result is a highly adaptive model that maintains unparalleled anatomical stability while rendering rich, deeply stylized, illustrative digital art. --- ## Changelog * **2026/07/05 - Added Aeterna Opus 0.2a** * Maintained prompt coherence from v0.1a for highly reliable, flexible text tracking. * Enhanced anatomy with more 'semi-accurate' proportions. * Minimized latent noise and artifacts along complex edges and fine lines * Low saturation has not been 'fixed' yet. Will work on it for v0.3a * **2026/06/29 - Initial Release** ## Model Details * **Developed by:** NeverWinter13 * **Model type:** Diffusion-based text-to-image generative model * **License:** [CreativeML Open RAIL++-M](https://huggingface.co/spaces/CompVis/stable-diffusion-license) * **Core Base:** SDXL Architecture (Ars Divina v7.2.4a x Indominus Rex XL Backbone) * **Training Methodology:** Cyclical continuous pre-training * **Primary Focus:** High-tier illustration, dynamic character staging, advanced multi-concept prompt adherence, and extreme structural stability. --- ## Downstream Use 1. Use it in [ComfyUI](https://github.com/comfyanonymous/ComfyUI) or [Stable Diffusion Webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) 2. Use it with `diffusers` --- ## 🖍️ Diffusers Installation ### 1. Install Required Libraries ```bash pip install diffusers transformers accelerate safetensors --upgrade ``` ### 2. Example code ```bash import torch from diffusers import StableDiffusionXLPipeline pipe = StableDiffusionXLPipeline.from_pretrained( "NeverWinter13/Aeterna-Opus", torch_dtype=torch.float16, use_safetensors=True ).to("cuda") prompt = "masterpiece, best quality, newest, 1girl, [clorinde] \\ [genshin impact], dynamic sword stance, dark fantasy background, dramatic cinematic lighting" negative_prompt = "(lowres:1.2), (worst quality:1.4), (low quality:1.4), (bad anatomy:1.4), bad hands, multiple views, watermark" image = pipe( prompt=prompt, negative_prompt=negative_prompt, width=832, height=1216, num_inference_steps=28, guidance_scale=5.0 ).images[0] image.save("aeterna_opus_output.png") ``` ## 🎨 Generation Guidelines & Recommendations Thanks to the *Indominus Rex* and *Ars Divina* DNA mixed with *Cagliostro/Onoma* training cycles, this model responds masterfully to both **highly descriptive natural language** and **structured Danbooru tags**. ## Generation Guidelines & Recommendations Thanks to the *Indominus Rex* and *Ars Divina* DNA mixed with *Cagliostro/Onoma* training cycles, this model responds masterfully to both **highly descriptive natural language** and **structured Danbooru tags**. ### Prompting Guide You can utilize standard descriptive natural language sentences or structured tags. For optimal character styling inspired by CagliostroLab's standards, structure your tags as follows: ``` 1girl/1boy, character name \[series name\], [your prompt whether natural language or tokens] ``` ### Quality Tags Add these tags at the start of your prompt: * **Positive Modifiers:** ``` masterpiece, best quality, newest ``` * **Positive Modifiers2:** ``` masterpiece, best quality, amazing quality, newest ``` ### Negatives You can utilize these negative embeddings or prompts or tags: * **Negative Framework:** ``` bad quality, worst quality, lowres, jpeg artifacts, bad anatomy, bad hands, multiple views, signature, watermark, censored, sketch, flat color, ugly, fat, blurry eyes, wrinkled skin ``` * **Negative Framework2:** ``` (lowres:1.2), (worst quality:1.4), (low quality:1.4), (bad anatomy:1.4), bad hands, multiple views, comic, jpeg artifacts, patreon logo, patreon username, web address, signature, watermark, text, logo, artist name, censored ``` ### Recommended Inference Settings * **Sampling Steps:** 26 - 30 steps * **Sampler:** Euler a * **CFG Scale:** 3.0 - 6.5 * **Hires.fix is not necessary (Per my case)** * **ADetailer is highly recommended** ### Recommended Resolutions | Orientation | Dimensions | Aspect Ratio | | :--- | :--- | :--- | | Square | 1024 x 1024 | 1:1 | | Landscape | 1152 x 896 | 9:7 | | | 1216 x 832 | 3:2 | | | 1344 x 768 | 7:4 | | | 1536 x 640 | 12:5 | | Portrait | 896 x 1152 | 7:9 | | | 832 x 1216 | 2:3 | | | 768 x 1344 | 4:7 | | | 640 x 1536 | 5:12 | ### Final Prompt Structure Example ``` masterpiece, best quality, newest, 1girl, tewi inaba \(touhou project\), outdoors, floating petals, charming smile, closed eyes, open mouth, volumetric light, lens flare, sunbeam, clouds, trees ``` ## 💖 Acknowledgments & Thanks This project would not have been possible without the groundbreaking work, innovative contributions, and comprehensive documentation provided by **Stability AI**, **Novel AI**, and the entire generative AI community. I am especially grateful for those who were with me from the beginning, starting from the **Stable Diffusion 1.5** days up through **Illustrious-XL**, fueling my interest in generative text-to-image models. Particularly: 1. **My Significant Other** 2. [OnomaAIResearch](https://huggingface.co/OnomaAIResearch) 3. [Cagliostro Labs](https://huggingface.co/cagliostrolab) 4. [nukeai1106](https://civitai.red/user/nukeai1106) 5. [GoofyAI](https://civitai.red/user/Goofy_Ai) 6. [Raelina](https://huggingface.co/raelina) 7. [DaoOwOarts](https://pixai.art/en/@dao0w0arts/artworks) 8. [Kohya_ss](https://github.com/bmaltais/kohya_ss) 9. [SeaArt AI](https://www.seaart.ai/) 10. [PixAI](https://pixai.art/) 11. [Moescape AI](https://moescape.ai/) 12. [Civitai](https://civitai.com/) Thank you. **Aeterna Opus** is a reflection of this 'random bullshit go' philosophy.