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SD-Trainer

SD-Trainer

✨ Enjoy Stable Diffusion Train! ✨

GitHub Repo stars GitHub forks license release

Download · Documents · 中文README

LoRA-scripts (a.k.a SD-Trainer)

LoRA & Dreambooth training GUI & scripts preset & one key training environment for kohya-ss/sd-scripts

✨NEW: Train WebUI

The REAL Stable Diffusion Training Studio. Everything in one WebUI.

Follow the installation guide below to install the GUI, then run run_gui.ps1(windows) or run_gui.sh(linux) to start the GUI.

image

Tensorboard WD 1.4 Tagger Tag Editor
image image image

Usage

Required Dependencies

Python 3.10 and Git

Clone repo with submodules

git clone --recurse-submodules https://github.com/Akegarasu/lora-scripts

✨ SD-Trainer GUI

Windows

Installation

Run install.ps1 will automatically create a venv for you and install necessary deps. If you are in China mainland, please use install-cn.ps1

Train

run run_gui.ps1, then program will open http://127.0.0.1:28000 automanticlly

Linux

Installation

Run install.bash will create a venv and install necessary deps.

Train

run bash run_gui.bash, then program will open http://127.0.0.1:28000 automanticlly

Legacy training through run script manually

Windows

Installation

Run install.ps1 will automatically create a venv for you and install necessary deps.

Train

Edit train.ps1, and run it.

Linux

Installation

Run install.bash will create a venv and install necessary deps.

Train

Training script train.sh will not activate venv for you. You should activate venv first.

source venv/bin/activate

Edit train.sh, and run it.

TensorBoard

Run tensorboard.ps1 will start TensorBoard at http://localhost:6006/

Program arguments

Parameter Name Type Default Value Description
--host str "127.0.0.1" Hostname for the server
--port int 28000 Port to run the server
--listen bool false Enable listening mode for the server
--skip-prepare-environment bool false Skip the environment preparation step
--disable-tensorboard bool false Disable TensorBoard
--disable-tageditor bool false Disable tag editor
--tensorboard-host str "127.0.0.1" Host to run TensorBoard
--tensorboard-port int 6006 Port to run TensorBoard
--localization str Localization settings for the interface
--dev bool false Developer mode to disale some checks