# lora-scripts
**Repository Path**: Sake809/lora-scripts
## Basic Information
- **Project Name**: lora-scripts
- **Description**: LoRA & Dreambooth training scripts & GUI use kohya-ss's trainer, for diffusion model.
- **Primary Language**: Python
- **License**: AGPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-01-11
- **Last Updated**: 2024-01-11
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README

# SD-Trainer
_✨ Enjoy Stable Diffusion Train! ✨_
Download
·
Documents
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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](https://github.com/kohya-ss/sd-scripts.git)
## ✨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.

| Tensorboard | WD 1.4 Tagger | Tag Editor |
| ------------ | ------------ | ------------ |
|  |  |  |
# Usage
### Required Dependencies
Python 3.10 and Git
### Clone repo with submodules
```sh
git clone --recurse-submodules https://github.com/Akegarasu/lora-scripts
```
## ✨ SD-Trainer GUI
### Windows
#### Installation
Run `install.ps1` will automaticilly 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](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](http://127.0.0.1:28000) automanticlly
## Legacy training through run script manually
### Windows
#### Installation
Run `install.ps1` will automaticilly 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.
```sh
source venv/bin/activate
```
Edit `train.sh`, and run it.
#### TensorBoard
Run `tensorboard.ps1` will start TensorBoard at http://localhost:6006/