Neta Lumina
Generate stunning anime and illustration-style images with Neta Lumina — a specialized text-to-image model optimized for character art, dynamic poses, and artistic styles. With support for artist tags, character references, and custom dimensions, it's the perfect tool for anime fans, illustrators, and creative content creators.
Why It Looks Great
- Anime & illustration focus: Optimized for character art, anime styles, and illustrative aesthetics.
- Artist style support: Reference specific artists using tags (e.g., @artistname:1.0) for style guidance.
- Character tags: Use character references for recognizable designs and features.
- Custom dimensions: Precise control over width and height for any aspect ratio.
- Dynamic compositions: Excels at foreshortening, action poses, and expressive perspectives.
- Prompt Enhancer: Built-in tool to refine and expand your descriptions automatically.
- Multiple formats: Export as JPEG, PNG, or WebP.
Parameters
| Parameter | Required | Description |
|---|
| prompt | Yes | Text description including style tags, character references, and scene details. |
| size | No | Custom dimensions with separate width and height controls. |
| width | No | Output width in pixels (e.g., 1024). |
| height | No | Output height in pixels (e.g., 1024). |
| seed | No | Random seed for reproducibility. Use -1 for random. |
| output_format | No | File format: jpeg, png, or webp. Default: jpeg. |
How to Use
- Write your prompt — include style tags, character references, and scene descriptions.
- Use Prompt Enhancer (optional) — click to automatically enrich your description.
- Set dimensions — adjust width and height sliders to your desired resolution.
- Set seed (optional) — use -1 for random, or a specific number to reproduce results.
- Choose output format — select jpeg, png, or webp based on your needs.
- Run — click the button to generate.
- Download — preview and save your image.
Pricing
Flat rate per image generation.
Best Use Cases
- Character Art — Create original characters or fan art with distinctive anime aesthetics.
- Dynamic Illustrations — Generate action poses, foreshortening, and expressive compositions.
- Style Exploration — Experiment with different artist styles using reference tags.
- Fan Art & Derivatives — Generate art featuring known characters with style variations.
- Concept Art — Rapid character and scene ideation for creative projects.
Example Prompts
- "foreshortening, This artwork by (@haneru:1.0) features character:#elphelt valentine in a playful and dynamic pose. The illustration showcases her upper body with a foreshortened perspective that emphasizes her outstretched hand holding food near her"
- "1girl, silver hair, red eyes, gothic lolita dress, sitting on throne, dramatic lighting, detailed background"
- "dynamic action pose, male warrior, sword slash motion blur, fantasy armor, epic battle scene"
- "cute chibi style, cat ears, pastel colors, simple background, kawaii expression"
- "portrait, detailed eyes, flowing hair, soft lighting, dreamy atmosphere, by (@artistname:0.8)"
Prompt Syntax Tips
| Syntax | Purpose | Example |
|---|
| (@artist:weight) | Reference artist style | (@haneru:1.0) |
| character:#name | Reference specific character | character:#elphelt valentine |
| 1girl, 1boy | Character count/gender | 1girl, blue hair |
| Descriptive tags | Scene and style details | dynamic pose, foreshortening |
Pro Tips for Best Results
- Use artist tags with weights (0.5-1.5) to control style influence strength.
- Combine character tags with style modifications for unique variations.
- Include composition terms: "foreshortening", "dynamic angle", "close-up", "full body".
- Describe specific features: hair color, eye color, clothing, accessories.
- Square dimensions (1024×1024) work well for portraits; adjust for full-body or scenes.
- Use PNG format for highest quality or WebP for smaller file sizes.
Notes
- Artist and character tags work best when the model has been trained on relevant data.
- Experiment with tag weights to find the right balance of style influence.
- Processing is fast and affordable — ideal for rapid iteration and exploration.
- Generation time may vary based on resolution and current queue load.