docs/CLI.md

--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)