--vace-1-3B--vace-1-3B# Command Line Reference This document covers all available command line options for WanGP. ## Basic Usage ```bash # 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 ```bash --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 ```bash --perc-reserved-mem-max FLOAT # Max percentage of RAM for reserved memory (< 0.5) ``` ## Lora Configuration ```bash --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 ```bash --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 ```bash --teacache MULTIPLIER # TeaCache speed multiplier: 0, 1.5, 1.75, 2.0, 2.25, 2.5 ``` ## Interface and Server Options ### Server Configuration ```bash --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 ```bash --lock-config # Prevent modifying video engine configuration from interface --theme THEME_NAME # UI theme: "default" or "gradio" ``` ## File and Directory Options ```bash --settings PATH # Path to folder containing default settings for all models --verbose LEVEL # Information level 0-2 (default: 1) ``` ## Examples ### Basic Usage Examples ```bash # 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 ```bash # 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 ```bash # 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 ```bash # 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) ```bash python wgp.py --attention sdpa ``` - Available by default with PyTorch - Good compatibility with all GPUs - Moderate performance ### Sage Attention ```bash python wgp.py --attention sage ``` - Requires Triton installation - 30% faster than SDPA - Small quality cost ### Sage2 Attention ```bash python wgp.py --attention sage2 ``` - Requires Triton and SageAttention 2.x - 40% faster than SDPA - Best performance option ### Flash Attention ```bash 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 ```bash # If advanced features don't work python wgp.py --attention sdpa --profile 4 --fp16 ``` ### Debug Mode ```bash # Maximum verbosity for troubleshooting python wgp.py --verbose 2 --check-loras ``` ### Memory Issue Debugging ```bash # Minimal memory usage python wgp.py --profile 4 --attention sdpa --perc-reserved-mem-max 0.2 ``` ## Configuration Files ### Settings Files Load custom settings: ```bash python wgp.py --settings /path/to/settings/folder ``` ### Lora Presets Create and share lora configurations: ```bash # 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 GPUs - `PYTORCH_CUDA_ALLOC_CONF` - CUDA memory allocation settings - `TRITON_CACHE_DIR` - Triton cache directory (for Sage attention)