Style LoRAs — Vision Document
This page describes the design vision for our Style LoRAs system, which will integrate with Amanda Co-Pilot's generative motion model post-launch. The Casual / Combat / Dance / Romance modules described below are the planned style adapters; the LoRA pipeline is in active training. See Amanda Co-Pilot for delivery timeline.
Low-Rank Adaptation (LoRA) enables fine-tuning of large pretrained models by training only a small number of additional parameters. Applied to motion synthesis, this allows domain-specific control without full model retraining.
What are Style LoRAs?
Style LoRAs are lightweight adapter modules that modify the base Kinetiq model to produce motion in specific styles. Instead of training a new model for each domain, we:
- Train a base model on diverse motion data
- Create small LoRA adapters for specific styles
- Inject the adapter at inference time
- Generate styled motion without base model changes
Available Style Modules
Casual
Everyday movement patterns:
- Walking variations (confident, relaxed, tired)
- Standing poses and idle animations
- Sitting and getting up
- Casual gestures and reactions
Best for: NPC idle animations, background characters, slice-of-life content
Combat
Martial arts and action sequences:
- Punches, kicks, and strikes
- Blocking and dodging
- Weapon handling (sword, staff, gun)
- Combat stances and transitions
Best for: Action games, fighting sequences, RPG combat
Dance
Choreographed and rhythmic movement:
- Club/party dancing
- Formal ballroom styles
- Contemporary and modern dance
- Synchronized group motion
Best for: Music videos, party scenes, performance content
Romance
Couples interaction and intimate gestures:
- Embracing and holding hands
- Dance partners
- Emotional reactions
- Close proximity interactions
Best for: Relationship content, drama scenes, social simulation
Gender Expression
Unlike models that encode gender as a binary switch, Kinetiq supports continuous gender expression through dedicated LoRA modules.
Why This Matters
Motion style varies independently of skeletal structure. A "masculine walk" or "feminine gesture" is a learned cultural pattern, not an anatomical constraint.
Available Expression Modules
- Neutral - Balanced expression, suitable for most content
- Masculine-leaning - Broader gestures, wider stance
- Feminine-leaning - Fluid movement, expressive hands
Gender expression LoRAs can be combined with style LoRAs (e.g., "feminine combat" or "masculine dance").
Using Style LoRAs
In the Editor
- Open the Kinetiq Editor
- Generate or import a base animation
- Select a Style LoRA from the dropdown
- Adjust the style weight (0.0 - 1.0)
- Preview and export
Style Weight
The style weight controls how much the LoRA affects output:
| Weight | Effect |
|---|---|
| 0.0 | No style influence (base model only) |
| 0.5 | Balanced blend |
| 1.0 | Full style influence |
| >1.0 | Exaggerated style (may cause artifacts) |
Combining Styles
Multiple LoRAs can be combined with weighted blending:
Final = Base + (0.7 × Combat) + (0.3 × Masculine)
This produces combat motion with a masculine expression undertone.
Technical Details
LoRA Architecture
- Rank: 16 (balance of quality vs. file size)
- Target Layers: Attention and feedforward modules
- Parameters: ~2M per adapter
- File Size: ~8 MB per style
Training Data
Each style LoRA is trained on curated subsets of our Ecological Interaction Data:
| Style | Training Hours | Sources |
|---|---|---|
| Casual | 500+ hours | Social interactions |
| Combat | 200+ hours | Martial arts, action |
| Dance | 300+ hours | Performances, clubs |
| Romance | 150+ hours | Couples, intimacy |
Requesting New Styles
We're continuously expanding our style library. To request a new style:
- Join our Discord
- Post in #feature-requests
- Describe the style with examples
- Vote on community suggestions
Popular requests may be prioritized for training.
Style LoRAs are available on all subscription tiers.