XVerse AI Documentation

Quick Start Guide

Get started with XVerse AI in just a few steps. This guide will help you understand the basics and start generating controlled multi-subject images.

1

Access the Model

Visit the Hugging Face repository or use our interactive demo to begin exploring XVerse capabilities.

2

Prepare Reference Images

Select clear, high-quality reference images of subjects you want to control in your generated images.

3

Generate and Control

Use text prompts to describe your desired scene and apply XVerse's multi-subject control features.

Technical Overview

Architecture

XVerse employs a novel text flow modulation mechanism that transforms reference images into token-specific modulation offsets. This approach enables precise control over multiple subjects without interfering with the underlying image generation process.

Core Components

  • 📊
    Text Flow Modulator

    Transforms reference images into token-specific offsets

  • 🎯
    Subject Controller

    Manages individual subject identity and attributes

  • 🔧
    Attribute Manipulator

    Controls semantic attributes like pose, style, and lighting

  • 🌟
    Generation Engine

    Base diffusion model for high-quality image synthesis

Key Features

Multi-Subject Control

Simultaneous control of multiple subjects without interference

Identity Preservation

Maintains consistent subject characteristics across variations

Attribute Independence

Modify individual attributes without affecting others

Usage Instructions

1Prepare Reference Images

Image Requirements

  • High resolution (512x512 minimum)
  • Clear subject visibility
  • Good lighting conditions
  • Minimal background clutter
  • Frontal or three-quarter pose preferred

Best Practices

  • Use multiple angles for better control
  • Ensure consistent lighting across references
  • Avoid heavily processed or filtered images
  • Include full body shots when possible

2Create Text Prompts

Prompt Structure

[Subject Description] + [Scene Context] + [Style Modifiers] + [Attribute Controls]
Good Examples
"A man in casual clothing standing in a modern office, professional lighting"
"Two people walking together in a park, sunset lighting, cinematic style"
Avoid
"Person" (too vague)
"Amazing beautiful perfect image" (overly generic)

3Configure Control Parameters

Identity Control

  • • Subject reference weight
  • • Identity preservation strength
  • • Feature consistency level

Attribute Control

  • • Pose modification
  • • Style transfer intensity
  • • Lighting adjustment

Generation Settings

  • • Resolution selection
  • • Number of iterations
  • • Guidance scale

Interactive Demo

Try XVerse AI directly in your browser with our interactive demo. No installation required.

Interactive demo powered by Hugging Face Spaces. Experience XVerse AI's capabilities in real-time.

API Reference

Model Access

Access XVerse AI through the Hugging Face Model Hub for integration into your applications.

Hugging Face Integration

from transformers import XVerseModel, XVerseTokenizer

# Load the model and tokenizer
model = XVerseModel.from_pretrained("ByteDance/XVerse")
tokenizer = XVerseTokenizer.from_pretrained("ByteDance/XVerse")

# Generate with multi-subject control
result = model.generate(
    prompt="Two people in a professional setting",
    reference_images=[image1, image2],
    control_weights=[0.8, 0.7]
)

Parameters

ParameterTypeDescription
promptstringText description of the desired image
reference_imageslistSubject reference images for control
control_weightslistControl strength for each subject (0.0-1.0)
resolutiontupleOutput image resolution (width, height)

Resources and Links

📄

Research Paper

Read the original research paper detailing XVerse's technical innovations and experimental results.

arxiv.org/abs/2506.21416 →
🔬

GitHub Repository

Access the source code, examples, and additional documentation on GitHub.

github.com/bytedance/XVerse →
🤗

Hugging Face Model

Access the pre-trained model and integration examples on Hugging Face.

huggingface.co/ByteDance/XVerse →
🌐

Official Website

Visit the official project website for additional information and updates.

bytedance.github.io/XVerse/ →
💬

Community Forum

Join discussions and get help from the XVerse AI community.

Coming Soon
📚

Tutorials

Step-by-step tutorials and advanced usage examples for XVerse AI.

Coming Soon

Support and Community

Need help with XVerse AI? Our community and support resources are here to assist you.

Getting Help

  • 📖Check this documentation first
  • 🐛Report issues on GitHub
  • 💡Join community discussions
  • 📧Contact our support team

Contributing

XVerse AI is an open research project. We welcome contributions from the community including bug reports, feature requests, and code improvements.

Get in Touch