Higgsfield Soul Character
0This skill allows users to train a face-faithful identity model that can be reused across all Soul-powered generations. It is intended for developers looking to create accurate identity representations in their applications.
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AI Identity Modeling
Quick InstallView Source
$ npx skills add https://github.com/higgsfield-ai/skills --skill higgsfield-soul-idOverview
About This Skill
Higgsfield Soul Character lets you train a personalized identity model from face photos that can be reused across all Soul-powered image and video generations. The skill captures a person's appearance into a reusable reference ID, which is then passed to generation models like text2image_soul_v2 or soul_cinematic_studio. Training requires 5–20 face photos from varied angles and lighting, and returns a reference ID for downstream use. This solves the problem of maintaining consistent identity across multiple generated outputs without manual face-swapping. Developers building avatar systems, digital twin applications, or identity-consistent content pipelines benefit most.
How to Use
Execute the installation command to add the skill and follow bootstrap steps.
Use Cases
Train a realistic character identity for gaming.
Create personalized avatars for social media.
Develop identity models for virtual assistants.
Tags
Setup & Installation
Quick Install
Terminal
$ npx skills add https://github.com/higgsfield-ai/skills --skill higgsfield-soul-idAlternative Install (Git Clone)
git clone https://github.com/higgsfield-ai/skillsRequirements
- Claude Code or compatible AI agent
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Train a Higgsfield Soul Character model for [COMPANY] using the following reference data: [REFERENCE_DATA]. Focus on preserving facial fidelity, emotional expressions, and unique mannerisms. Generate a reusable identity model that can be applied to Soul-powered generations in [INDUSTRY] applications.
Example Output
### Higgsfield Soul Character Model - Training Report **Model ID:** `higgsfield_soul_001` **Fidelity Score:** 98.7% (Face), 94.2% (Expressions), 96.1% (Mannerisms) **Training Data:** 1,247 high-resolution images + 89 video clips (30fps) #### Key Features Preserved: - **Facial Structure:** Symmetrical features, mole on left cheek, slight asymmetry in smile - **Expressions:** Calm neutral, warm smile, focused concentration, subtle eyebrow raise - **Mannerisms:** Head tilt when listening, frequent eye contact, hand gestures during speech #### Recommended Use Cases: - Interactive customer service avatars for [COMPANY]'s retail platform - Virtual brand ambassadors for [INDUSTRY] marketing campaigns - Personalized learning companions for [COMPANY]'s education app **Next Steps:** Deploy model via API endpoint `soul.higgsfield.ai/v1/generate` with parameter `--style fidelity`.
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