HunYuan3D AI Installation Guide: Step-by-Step Setup Instructions
Introduction
This comprehensive guide walks you through the process of installing HunYuan3D AI on your local system. For alternative deployment methods, see our guides on Docker deployment or explore the technical architecture.
System Requirements
Hardware Requirements
- CPU: 8+ cores (Intel i7/i9 or AMD Ryzen 7/9 recommended)
- GPU: NVIDIA RTX 2060 or better (8GB+ VRAM)
- RAM: 16GB minimum (32GB recommended)
- Storage: 50GB+ SSD space
- Internet: Stable connection for initial setup
Software Requirements
- Operating System:
- Windows 10/11 (64-bit)
- Ubuntu 20.04/22.04 LTS
- macOS 12+ (Apple Silicon supported)
- Python: Version 3.8-3.10
- CUDA: Version 11.4 or higher
- Git: Latest stable version
Pre-Installation Steps
1. Environment Setup
# Create and activate virtual environment
python -m venv hunyuan3d-env
source hunyuan3d-env/bin/activate # Linux/macOS
.\hunyuan3d-env\Scripts\activate # Windows
2. CUDA Installation
- Download CUDA Toolkit from NVIDIA website
- Install CUDA following platform-specific instructions
- Verify installation:
nvidia-smi
nvcc --version
3. Dependencies Installation
# Install required system packages
pip install --upgrade pip
pip install wheel setuptools
Installation Process
1. Clone Repository
git clone https://github.com/tencent/Hunyuan3D-2
cd Hunyuan3D-2
2. Install Requirements
pip install -r requirements.txt
3. Install HunYuan3D
python setup.py install
4. Verify Installation
python -c "import hunyuan3d; print(hunyuan3d.__version__)"
Post-Installation Configuration
1. Environment Variables
# Linux/macOS
export HUNYUAN3D_HOME=/path/to/hunyuan3d
export CUDA_VISIBLE_DEVICES=0
# Windows
set HUNYUAN3D_HOME=C:\path\to\hunyuan3d
set CUDA_VISIBLE_DEVICES=0
2. Model Downloads
# Download pre-trained models
python -m hunyuan3d.utils.download_models
3. Configuration File Setup
# config.yaml
model:
type: "standard"
precision: "float16"
cache_dir: "./model_cache"
system:
gpu_memory_fraction: 0.8
num_threads: 4
log_level: "INFO"
Testing Installation
1. Run Basic Test
python -m hunyuan3d.tests.basic_test
2. Generate Test Model
import hunyuan3d
# Initialize generator
generator = hunyuan3d.Generator()
# Generate simple model
result = generator.generate(
prompt="simple cube",
output_format="obj"
)
Common Issues and Solutions
CUDA Related Issues
-
Error: CUDA not found
- Solution: Verify CUDA installation and PATH
echo $PATH # Check CUDA in path nvidia-smi # Verify GPU access
-
Error: GPU memory insufficient
- Solution: Adjust memory usage in config
system: gpu_memory_fraction: 0.6 # Reduce from 0.8
Python Environment Issues
-
Error: Package conflicts
- Solution: Clean installation
pip uninstall hunyuan3d pip install --no-cache-dir hunyuan3d
-
Error: Version mismatch
- Solution: Check compatibility
pip list | grep torch pip install torch==1.12.0 # Use compatible version
System Integration Issues
-
Error: Path not found
- Solution: Verify environment setup
echo $HUNYUAN3D_HOME ls $HUNYUAN3D_HOME/models
-
Error: Permission denied
- Solution: Check file permissions
chmod +x setup.py sudo chown -R user:user .
Optimization Tips
Performance Tuning
- GPU Optimization
system:
cuda_cache_size: "2GB"
precision: "float16"
- Memory Management
system:
batch_size: 1
worker_threads: 2
Resource Management
- Cache Configuration
cache:
model_cache_size: "5GB"
texture_cache_size: "2GB"
- Log Management
logging:
level: "INFO"
file: "hunyuan3d.log"
Next Steps
1. Integration Setup
2. Learning Resources
Support and Updates
Getting Help
- GitHub Issues: Report technical problems
- Community Forum: Ask questions
- Documentation: Reference guides
Staying Updated
- Watch GitHub repository
- Join community channels
- Subscribe to release notifications
Conclusion
Following this installation guide should give you a fully functional HunYuan3D AI setup. If you encounter any issues not covered here, please check our community forum or raise an issue on GitHub.
This guide is part of our HunYuan3D AI documentation series. For an overview of the system, see our introduction.