Quick and easy CLI inference that just works™ for a variety of Diffusers models
- Verified working across many models
- AuraFlow
- FLUX
- Hunyuan
- Kandinsky
- Kolors
- Lumina T2X
- Pixart (Alpha/Sigma)
- Stable Cascade
- Stable Diffusion (1.5/2.1)
- Stable Diffusion 3
- Stable Diffusion XL
- No refiner
- Wuerstchen
- Other Diffusers format models will likely work to varying degrees
- Multi-lora fusion using
peftfor minimal performance loss - Features all of the most common generation parameters
- Includes many advanced generation parameters
- 1, 2, 3, 4, 5, 6, 7, 8-bit quantization
- PAG / Perturbed-Attention Guidance
- Many latent augmentation params
- Many post processing effects
- Iterate over most parameters and create grids
- Expand prompts with
photo of {all|of|these}orphoto of [one|of|these] - Load settings from JSON, TOML, PNG
- Extremely small 1-shot script using
acceleratefor hot loading models - Targeted AMD/ROCm optimizations
- NVIDIA/CUDA does not need additional optimizations
- ControlNet, Inpaint
- Multi-stage models: DFIF Stage 2, SDXL Refiner
- Server/API for a perpetual instance
- 100% maximum throughput
- 1-click installer
- MacOS/MPS and Intel OneAPI may not function properly
This project only supports pip based installs on Python 3.11+
> git clone https://github.com/Beinsezii/quickdif.git
> cd ./quickdif/> python3 -m venv ./venv
# alternatively, it's recommended to use the full virtualenv if you have it
> virtualenv ./venv# replace with appropriate activation script for other shells
> source ./venv/bin/activate
# It's recommended to first install torch using the recommended commands from https://pytorch.org/get-started/locally/
> pip install torch --index-url https://download.pytorch.org/whl/rocm6.0 # AMD example
# finally
> pip install -e .
> deactivate
> ./quickdif.sh "kitten"
# Windows users will instead have to invoke Python directly
> python quickdif.py "kitten"Additionally, you may use the project as a python module
pip install git+https://github.com/Beinsezii/quickdif.git
python -m quickdif "kitten"# See all options. Always refer to the script help over the other examples in this README
> ./quickdif.sh --help
# Run with defaults
> ./quickdif.sh "high resolution dslr photograph of pink roses in the misty rain"
# Custom model
> ./quickdif.sh "analogue photograph of a kitteon on the beach in golden hour sun rays" -m "ptx0/terminus-xl-gamma-v1"
# Single files work for Stable Diffusion
> ./quickdif.sh "colorful fantasy artwork side profile of a feminine robot in a dark cyberpunk city" -m ./checkpoints/sd15/dreamshaper-v6.safetensors
# Four dog and four cat images at twenty steps
> ./quickdif.sh "photo of a dog" "painting of a cat" -B 4 -s 20
# Colored latent for an offset noise effect
> ./quickdif.sh "underwater photograph of a dark cave full of bioluminescent glowing mushrooms" -g 9.0 -s 30 -C black -c 0.8
# Compile for a long job
> ./quickdif.sh $(cat prompts.txt) --compile
# Export favorite settings to the defaults JSON
> ./quickdif.sh -m "stabilityai/stable-cascade" -s 20 -n "blurry, noisy, cropped" --json ./quickdif.json
# Save a style to a custom JSON
> ./quickdif.sh "fantasy artwork of a kitten wearing gothic plate armor" -g 10 -G 0.5 --json ./epic_kitten.json
# Merge multiple configs
> ./quickdif.sh -I underwater_cave.png epic_kitten.json| Question | Answer |
|---|---|
| Why not X popular UI? | SD.Next's diffusers backend is extremely buggy/broken in multiple areas and InvokeAI (+non-diffusers UIs) only really supports Stable Diffusion. |
| Windows? | The python script should work just fine but you'll need to set up the powershell/CMD stuff on your own. |
| Gradio? | No. If a UI ever gets made for this it'll be its own separate entity that interfaces via API. Cramming a bad gradio interface into the main script wont do anyone any favors |
| Feature XYZ? | Maybe. Things in the Not Including list may come eventually™ if this script winds up being useful enough |