Spaces:
Configuration error
Configuration error
File size: 2,920 Bytes
2b67076 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 |
# Installation Guide
This guide covers installation for different GPU generations and operating systems.
## Requirements
- Python 3.10.9
- Conda or Python venv
- Compatible GPU (RTX 10XX or newer recommended)
## Installation for RTX 10XX to RTX 50XX (Stable)
This installation uses PyTorch 2.7.0 which is well-tested and stable.
### Step 1: Download and Setup Environment
```shell
# Clone the repository
git clone https://github.com/deepbeepmeep/Wan2GP.git
cd Wan2GP
# Create Python 3.10.9 environment using conda
conda create -n wan2gp python=3.10.9
conda activate wan2gp
```
### Step 2: Install PyTorch
```shell
# Install PyTorch 2.7.0 with CUDA 12.8
pip install torch==2.7.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu128
```
### Step 3: Install Dependencies
```shell
# Install core dependencies
pip install -r requirements.txt
```
### Step 4: Optional Performance Optimizations
#### Sage Attention (30% faster), don't install with RTX 50xx as it is not compatible
```shell
# Windows only: Install Triton
pip install triton-windows
# For both Windows and Linux
pip install sageattention==1.0.6
```
#### Sage 2 Attention (40% faster)
```shell
# Windows
pip install triton-windows
pip install https://github.com/woct0rdho/SageAttention/releases/download/v2.1.1-windows/sageattention-2.1.1+cu126torch2.6.0-cp310-cp310-win_amd64.whl
# Linux (manual compilation required)
python -m pip install "setuptools<=75.8.2" --force-reinstall
git clone https://github.com/thu-ml/SageAttention
cd SageAttention
pip install -e .
```
#### Flash Attention
```shell
# May require CUDA kernel compilation on Windows
pip install flash-attn==2.7.2.post1
```
## Attention Modes
WanGP supports several attention implementations:
- **SDPA** (default): Available by default with PyTorch
- **Sage**: 30% speed boost with small quality cost
- **Sage2**: 40% speed boost
- **Flash**: Good performance, may be complex to install on Windows
### Attention GPU Compatibility
- RTX 10XX, 20XX: SDPA
- RTX 30XX, 40XX: SDPA, Flash Attention, Xformers, Sage, Sage2
- RTX 50XX: SDPA, SDPA, Flash Attention, Xformers, Sage2
## Performance Profiles
Choose a profile based on your hardware:
- **Profile 3 (LowRAM_HighVRAM)**: Loads entire model in VRAM, requires 24GB VRAM for 8-bit quantized 14B model
- **Profile 4 (LowRAM_LowVRAM)**: Default, loads model parts as needed, slower but lower VRAM requirement
## Troubleshooting
### Sage Attention Issues
If Sage attention doesn't work:
1. Check if Triton is properly installed
2. Clear Triton cache
3. Fallback to SDPA attention:
```bash
python wgp.py --attention sdpa
```
### Memory Issues
- Use lower resolution or shorter videos
- Enable quantization (default)
- Use Profile 4 for lower VRAM usage
- Consider using 1.3B models instead of 14B models
For more troubleshooting, see [TROUBLESHOOTING.md](TROUBLESHOOTING.md)
|