A newer version of the Gradio SDK is available:
5.34.2
--vace-1-3B--vace-1-3B# Command Line Reference
This document covers all available command line options for WanGP.
Basic Usage
# Default launch
python wgp.py
# Specific model modes
python wgp.py --i2v # Image-to-video
python wgp.py --t2v # Text-to-video (default)
python wgp.py --t2v-14B # 14B text-to-video model
python wgp.py --t2v-1-3B # 1.3B text-to-video model
python wgp.py --i2v-14B # 14B image-to-video model
python wgp.py --i2v-1-3B # Fun InP 1.3B image-to-video model
python wgp.py --vace-1-3B # VACE ControlNet 1.3B model
Model and Performance Options
Model Configuration
--quantize-transformer BOOL # Enable/disable transformer quantization (default: True)
--compile # Enable PyTorch compilation (requires Triton)
--attention MODE # Force attention mode: sdpa, flash, sage, sage2
--profile NUMBER # Performance profile 1-5 (default: 4)
--preload NUMBER # Preload N MB of diffusion model in VRAM
--fp16 # Force fp16 instead of bf16 models
--gpu DEVICE # Run on specific GPU device (e.g., "cuda:1")
Performance Profiles
- Profile 1: Load entire current model in VRAM and keep all unused models in reserved RAM for fast VRAM tranfers
- Profile 2: Load model parts as needed, keep all unused models in reserved RAM for fast VRAM tranfers
- Profile 3: Load entire current model in VRAM (requires 24GB for 14B model)
- Profile 4: Default and recommended, load model parts as needed, most flexible option
- Profile 5: Minimum RAM usage
Memory Management
--perc-reserved-mem-max FLOAT # Max percentage of RAM for reserved memory (< 0.5)
Lora Configuration
--lora-dir PATH # Path to Wan t2v loras directory
--lora-dir-i2v PATH # Path to Wan i2v loras directory
--lora-dir-hunyuan PATH # Path to Hunyuan t2v loras directory
--lora-dir-hunyuan-i2v PATH # Path to Hunyuan i2v loras directory
--lora-dir-ltxv PATH # Path to LTX Video loras directory
--lora-preset PRESET # Load lora preset file (.lset) on startup
--check-loras # Filter incompatible loras (slower startup)
Generation Settings
Basic Generation
--seed NUMBER # Set default seed value
--frames NUMBER # Set default number of frames to generate
--steps NUMBER # Set default number of denoising steps
--advanced # Launch with advanced mode enabled
Advanced Generation
--teacache MULTIPLIER # TeaCache speed multiplier: 0, 1.5, 1.75, 2.0, 2.25, 2.5
Interface and Server Options
Server Configuration
--server-port PORT # Gradio server port (default: 7860)
--server-name NAME # Gradio server name (default: localhost)
--listen # Make server accessible on network
--share # Create shareable HuggingFace URL for remote access
--open-browser # Open browser automatically when launching
Interface Options
--lock-config # Prevent modifying video engine configuration from interface
--theme THEME_NAME # UI theme: "default" or "gradio"
File and Directory Options
--settings PATH # Path to folder containing default settings for all models
--verbose LEVEL # Information level 0-2 (default: 1)
Examples
Basic Usage Examples
# Launch with specific model and loras
python wgp.py --t2v-14B --lora-preset mystyle.lset
# High-performance setup with compilation
python wgp.py --compile --attention sage2 --profile 3
# Low VRAM setup
python wgp.py --t2v-1-3B --profile 4 --attention sdpa
# Multiple images with custom lora directory
python wgp.py --i2v --multiple-images --lora-dir /path/to/shared/loras
Server Configuration Examples
# Network accessible server
python wgp.py --listen --server-port 8080
# Shareable server with custom theme
python wgp.py --share --theme gradio --open-browser
# Locked configuration for public use
python wgp.py --lock-config --share
Advanced Performance Examples
# Maximum performance (requires high-end GPU)
python wgp.py --compile --attention sage2 --profile 3 --preload 2000
# Optimized for RTX 2080Ti
python wgp.py --profile 4 --attention sdpa --teacache 2.0
# Memory-efficient setup
python wgp.py --fp16 --profile 4 --perc-reserved-mem-max 0.3
TeaCache Configuration
# Different speed multipliers
python wgp.py --teacache 1.5 # 1.5x speed, minimal quality loss
python wgp.py --teacache 2.0 # 2x speed, some quality loss
python wgp.py --teacache 2.5 # 2.5x speed, noticeable quality loss
python wgp.py --teacache 0 # Disable TeaCache
Attention Modes
SDPA (Default)
python wgp.py --attention sdpa
- Available by default with PyTorch
- Good compatibility with all GPUs
- Moderate performance
Sage Attention
python wgp.py --attention sage
- Requires Triton installation
- 30% faster than SDPA
- Small quality cost
Sage2 Attention
python wgp.py --attention sage2
- Requires Triton and SageAttention 2.x
- 40% faster than SDPA
- Best performance option
Flash Attention
python wgp.py --attention flash
- May require CUDA kernel compilation
- Good performance
- Can be complex to install on Windows
Troubleshooting Command Lines
Fallback to Basic Setup
# If advanced features don't work
python wgp.py --attention sdpa --profile 4 --fp16
Debug Mode
# Maximum verbosity for troubleshooting
python wgp.py --verbose 2 --check-loras
Memory Issue Debugging
# Minimal memory usage
python wgp.py --profile 4 --attention sdpa --perc-reserved-mem-max 0.2
Configuration Files
Settings Files
Load custom settings:
python wgp.py --settings /path/to/settings/folder
Lora Presets
Create and share lora configurations:
# Load specific preset
python wgp.py --lora-preset anime_style.lset
# With custom lora directory
python wgp.py --lora-preset mystyle.lset --lora-dir /shared/loras
Environment Variables
While not command line options, these environment variables can affect behavior:
CUDA_VISIBLE_DEVICES- Limit visible GPUsPYTORCH_CUDA_ALLOC_CONF- CUDA memory allocation settingsTRITON_CACHE_DIR- Triton cache directory (for Sage attention)