mirror of
https://github.com/kohya-ss/sd-scripts.git
synced 2026-04-16 00:49:40 +00:00
145 lines
5.9 KiB
Markdown
145 lines
5.9 KiB
Markdown
This repository contains training, generation and utility scripts for Stable Diffusion.
|
|
|
|
[__Change History__](#change-history) is moved to the bottom of the page.
|
|
更新履歴は[ページ末尾](#change-history)に移しました。
|
|
|
|
[日本語版README](./README-ja.md)
|
|
|
|
For easier use (GUI and PowerShell scripts etc...), please visit [the repository maintained by bmaltais](https://github.com/bmaltais/kohya_ss). Thanks to @bmaltais!
|
|
|
|
This repository contains the scripts for:
|
|
|
|
* DreamBooth training, including U-Net and Text Encoder
|
|
* Fine-tuning (native training), including U-Net and Text Encoder
|
|
* LoRA training
|
|
* Texutl Inversion training
|
|
* Image generation
|
|
* Model conversion (supports 1.x and 2.x, Stable Diffision ckpt/safetensors and Diffusers)
|
|
|
|
__Stable Diffusion web UI now seems to support LoRA trained by ``sd-scripts``.__ (SD 1.x based only) Thank you for great work!!!
|
|
|
|
## About requirements.txt
|
|
|
|
These files do not contain requirements for PyTorch. Because the versions of them depend on your environment. Please install PyTorch at first (see installation guide below.)
|
|
|
|
The scripts are tested with PyTorch 1.12.1 and 1.13.0, Diffusers 0.10.2.
|
|
|
|
## Links to how-to-use documents
|
|
|
|
All documents are in Japanese currently, and CUI based.
|
|
|
|
* [DreamBooth training guide](./train_db_README-ja.md)
|
|
* [Step by Step fine-tuning guide](./fine_tune_README_ja.md):
|
|
Including BLIP captioning and tagging by DeepDanbooru or WD14 tagger
|
|
* [training LoRA](./train_network_README-ja.md)
|
|
* [training Textual Inversion](./train_ti_README-ja.md)
|
|
* note.com [Image generation](https://note.com/kohya_ss/n/n2693183a798e)
|
|
* note.com [Model conversion](https://note.com/kohya_ss/n/n374f316fe4ad)
|
|
|
|
## Windows Required Dependencies
|
|
|
|
Python 3.10.6 and Git:
|
|
|
|
- Python 3.10.6: https://www.python.org/ftp/python/3.10.6/python-3.10.6-amd64.exe
|
|
- git: https://git-scm.com/download/win
|
|
|
|
Give unrestricted script access to powershell so venv can work:
|
|
|
|
- Open an administrator powershell window
|
|
- Type `Set-ExecutionPolicy Unrestricted` and answer A
|
|
- Close admin powershell window
|
|
|
|
## Windows Installation
|
|
|
|
Open a regular Powershell terminal and type the following inside:
|
|
|
|
```powershell
|
|
git clone https://github.com/kohya-ss/sd-scripts.git
|
|
cd sd-scripts
|
|
|
|
python -m venv venv
|
|
.\venv\Scripts\activate
|
|
|
|
pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116
|
|
pip install --upgrade -r requirements.txt
|
|
pip install -U -I --no-deps https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl
|
|
|
|
cp .\bitsandbytes_windows\*.dll .\venv\Lib\site-packages\bitsandbytes\
|
|
cp .\bitsandbytes_windows\cextension.py .\venv\Lib\site-packages\bitsandbytes\cextension.py
|
|
cp .\bitsandbytes_windows\main.py .\venv\Lib\site-packages\bitsandbytes\cuda_setup\main.py
|
|
|
|
accelerate config
|
|
```
|
|
|
|
update: ``python -m venv venv`` is seemed to be safer than ``python -m venv --system-site-packages venv`` (some user have packages in global python).
|
|
|
|
Answers to accelerate config:
|
|
|
|
```txt
|
|
- This machine
|
|
- No distributed training
|
|
- NO
|
|
- NO
|
|
- NO
|
|
- all
|
|
- fp16
|
|
```
|
|
|
|
note: Some user reports ``ValueError: fp16 mixed precision requires a GPU`` is occurred in training. In this case, answer `0` for the 6th question:
|
|
``What GPU(s) (by id) should be used for training on this machine as a comma-separated list? [all]:``
|
|
|
|
(Single GPU with id `0` will be used.)
|
|
|
|
### about PyTorch and xformers
|
|
|
|
Other versions of PyTorch and xformers seem to have problems with training.
|
|
If there is no other reason, please install the specified version.
|
|
|
|
## Upgrade
|
|
|
|
When a new release comes out you can upgrade your repo with the following command:
|
|
|
|
```powershell
|
|
cd sd-scripts
|
|
git pull
|
|
.\venv\Scripts\activate
|
|
pip install --use-pep517 --upgrade -r requirements.txt
|
|
```
|
|
|
|
Once the commands have completed successfully you should be ready to use the new version.
|
|
|
|
## Credits
|
|
|
|
The implementation for LoRA is based on [cloneofsimo's repo](https://github.com/cloneofsimo/lora). Thank you for great work!!!
|
|
|
|
## License
|
|
|
|
The majority of scripts is licensed under ASL 2.0 (including codes from Diffusers, cloneofsimo's), however portions of the project are available under separate license terms:
|
|
|
|
[Memory Efficient Attention Pytorch](https://github.com/lucidrains/memory-efficient-attention-pytorch): MIT
|
|
|
|
[bitsandbytes](https://github.com/TimDettmers/bitsandbytes): MIT
|
|
|
|
[BLIP](https://github.com/salesforce/BLIP): BSD-3-Clause
|
|
|
|
## Change History
|
|
|
|
- 22 Feb. 2023, 2023/2/22:
|
|
- Refactor optmizer options. Thanks to mgz-dev!
|
|
- Add ``--optimizer_type`` option for each training script. Please see help. Japanese documentation is here.
|
|
- ``--use_8bit_adam`` and ``--use_lion_optimizer`` options also work, but override above option.
|
|
- Add SGDNesterov and its 8bit.
|
|
- Add D-Adaptation optimizer. Thanks to BootsofLagrangian and all!
|
|
- Please see https://github.com/kohya-ss/sd-scripts/issues/181 for details.
|
|
- Add AdaFactor optimizer. Thanks to Toshiaki!
|
|
- オプティマイザ関連のオプションを見直しました。mgz-dev氏に感謝します。
|
|
- ``--optimizer_type`` を各学習スクリプトに追加しました。ドキュメントはこちら。
|
|
- ``--use_8bit_adam`` と ``--use_lion_optimizer`` のオプションは依然として動作しますがoptimizer_typeを上書きしますのでご注意ください。
|
|
- SGDNesterov オプティマイザおよびその8bit版を追加しました。
|
|
- D-Adaptation オプティマイザを追加しました。BootsofLagrangian 氏および諸氏に感謝します。
|
|
- こちらのissueもあわせてご覧ください。 https://github.com/kohya-ss/sd-scripts/issues/181
|
|
- AdaFactor オプティマイザを追加しました。Toshiaki氏に感謝します。
|
|
|
|
Please read [Releases](https://github.com/kohya-ss/sd-scripts/releases) for recent updates.
|
|
最近の更新情報は [Release](https://github.com/kohya-ss/sd-scripts/releases) をご覧ください。
|