Vete ┃ Crimson Oath (ILL & ANM)
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v.0.1 ANM

Vete ┃ Crimson Oath (ILL & ANM)

Vetehine
Creator
⭐ 0.0
⬇ 980 Downloads
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🖼 24 Images

About this model

Home of this model

moescape.ai is the primary home of this model and a broader collection of additional models. Many of these releases are exclusive to this platform and are not available elsewhere.
More information and related work can be found on my homepage: Ozia.

Creator: Vetehine

Discord: Vetehine

Linktree: />

Support

Tips help keep me going and allow me to create even better models and LoRAs for the community. Even small support makes a difference.


Please let me know what you think about this Model in the comments.


📋 Usage Guidelines

Merge Friendly: You are free to use this model in your own merges and creative projects.

Commercial Use: Do not resell this model or sell direct merges of it as paid content.

🤝 Credit: Credit is not required, but it is appreciated.


Vete ┃ Crimson Oath ILL is a semi-realistic character model built around controlled contrast, cinematic lighting, and emotionally charged atmospheres. It focuses on realism with stylized polish, blending soft facial structure with sharp material definition and deliberate light placement. The result is a model that feels grounded, intimate, and dramatic without drifting into anime or exaggerated stylization.

This model excels in low-light and mixed-light environments. Shadows are deep but readable, preserving form instead of crushing detail. Highlights are clean and intentional, wrapping naturally around skin, hair, fabric, and reflective surfaces. Skin rendering remains smooth and lifelike, avoiding plastic or waxy artifacts, while still holding a subtle glow under directional or ambient lighting. Eyes retain clarity and depth even in darker scenes, with controlled luminance rather than artificial glow.

Crimson Oath is not color-locked or red-biased, despite its name. While it performs beautifully with warm, crimson, and candlelit palettes, it is equally stable with cool blues, neutral whites, night city lighting, and soft daylight. Whites remain clean, blacks stay rich and stable, and midtones transition smoothly without banding or color bleed.

Material rendering is a core strength. Leather, lace, metal, glass, smoke, fabric, and skin all maintain clear separation. Jewelry and metallic accents catch light precisely without overpowering the scene. Hair stays well-defined with natural shine and strand separation, even under harsh rim light or low-key setups.

Stylistically, Crimson Oath supports a wide emotional range: dark romance, sacred and profane aesthetics, gothic interiors, modern night scenes, ritualistic or symbolic imagery, and intimate portrait work. It is equally effective for cinematic compositions and close-up character studies, maintaining structure and clarity across framing styles.

This model is stable enough to be used as-is for finished artwork, but it is also engineered to merge cleanly. As a merge component, it adds contrast discipline, light control, material realism, and emotional weight to other semi-realistic bases without overpowering them.

Crimson Oath is intentional, controlled, and expressive. It is designed for creators who want atmosphere without noise, darkness without loss of detail, and realism that still carries mood and presence.


“Adetailer ensures cleaner, more accurate faces and eyes.”


Illustrious-XL

AI Image Generation Settings Guide

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Clip Skip - 2

DPM++ 2M Karras / Euler Ancestral / Restart

Sampling Steps - 25-66

Cfg - 6-7


Hires-

R-ESRGAN 4x+ Anime6B, 4x-AnimeSharp

Steps 10 - 20

Denoising 0.2 - 0.3


ANIMA


Recommended settings:

CFG: 4–6

Steps: 30–50

Resolution range: 512–1536


Recommended samplers:

  • er_sde

  • euler_a

  • dpmpp_2m_sde_gpu


er_sde tends to produce cleaner anime-style linework and flatter color control.

euler_a often gives softer lines and a more painterly/2.5D feel.

dpmpp_2m_sde_gpu can create more experimental and creative outputs depending on prompting.


The model responds well to both tag-based prompting and natural language prompting, including mixed prompt structures.

Recommended prompt structure:

[quality/meta tags] → [subject] → [character/series] → [artist/style] → [general details] → [lighting/composition]

Example:

masterpiece, best quality, newest, safe, 1girl, original character, @artistname, white hair, black dress, glowing eyes, cinematic lighting, red moon, wind, night, detailed background


Natural language prompting also works very well:

A pale anime girl with long white hair standing under a crimson moon at night. Cinematic lighting, dark atmosphere, glowing red eyes, wind blowing through her hair, highly detailed illustration.


Mixed prompting:

masterpiece, best quality, newest, 1girl, white hair, black dress, glowing eyes.

A dark fantasy anime scene with cinematic lighting and red atmospheric fog.


Recommended quality/meta tags:

* masterpiece

* best quality

* newest

* highres

* absurdres

* safe / sensitive / nsfw / explicit


Recommended composition and atmosphere tags:

* cinematic lighting

* rim lighting

* depth of field

* dramatic angle

* dutch angle

* off center

* dynamic pose

* wind

* glowing

* blurry background

* bokeh

* atmospheric

* dramatic shadows


Artist prompting:

Artist tags generally work better using:

@artistname


Prompt weighting is supported, though stronger weights may work better than standard SDXL-style prompting.

Example:

(chibi:2)

(red eyes:1.8)


Time period tags

Specific year

year 2025, year 2024, ...


Period

newest, recent, mid, early, old


Meta tags

highres, absurdres, anime screenshot, jpeg artifacts, official art, etc


Safety tags

safe, sensitive, nsfw, explicit


The model generally performs better with:

* clean prompts

* focused styles

* clear character descriptions

* strong lighting descriptions

* balanced atmosphere tags


Overloading prompts with excessive conflicting tags can reduce consistency. Simpler prompts often produce cleaner results.


Legal & Usage Disclaimer

By accessing, using, generating with, or merging this model, you agree to these terms in full, regardless of whether you have read or acknowledged this notice.

This model is provided “as is,” without any warranties, express or implied, including but not limited to fitness for a particular purpose, legality of outputs, or compliance with platform policies.

Under no circumstances shall the author be held liable for any direct, indirect, incidental, consequential, special, or exemplary damages arising from or related to the use, misuse, or inability to use this model. This includes, without limitation, any content generated, modified, merged, distributed, or otherwise produced through the model, as well as any loss of data, loss of profits, reputational harm, legal claims, or third-party disputes resulting from such use.

This limitation of liability applies to all uses of the model, including but not limited to merging, fine-tuning, redistribution, or integration into other works or systems.

You are solely responsible for ensuring that your use complies with all applicable laws, regulations, and platform guidelines.

This disclaimer applies to all Vetehine models and LoRAs, whether or not this notice is explicitly included with a specific model or release.



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