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.
![image](https://github.com/Akegarasu/lora-scripts/assets/36563862/d3fcf5ad-fb8f-4e1d-81f9-c903376c19c6)
| Tensorboard | WD 1.4 Tagger | Tag Editor |
| ------------ | ------------ | ------------ |
| ![image](https://github.com/Akegarasu/lora-scripts/assets/36563862/b2ac5c36-3edf-43a6-9719-cb00b757fc76) | ![image](https://github.com/Akegarasu/lora-scripts/assets/36563862/9504fad1-7d77-46a7-a68f-91fbbdbc7407) | ![image](https://github.com/Akegarasu/lora-scripts/assets/36563862/4597917b-caa8-4e90-b950-8b01738996f2) |
# 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 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](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 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.
```sh
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 |