Kohya-ss-sd-scripts

22 Jan. 2023, 2023/1/22
- Fix script to check LoRA weights check_lora_weights.py. Some layer weights were shown as 0.0 even if the layer is trained, because of the overflow of torch.mean. Sorry for the confusion.
- Noe the script shows the mean of the absolute values of the weights, and the minimum of the absolute values of the weights.
- LoRAの重みをチェックするスクリプト check_lora_weights.py を修正しました。一部のレイヤーで学習されているにもかかわらず重みが 0.0 と表示されていました。混乱を招き申し訳ありません。
- スクリプトを「重みの絶対の平均」と「重みの絶対値の最小値」を表示するよう修正しました。

Please read Releases for recent updates. 最近の更新情報は Release をご覧ください。

日本語版README

For easier use (GUI and PowerShell scripts etc...), please visit the repository maintained by bmaltais. 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
image generation
model conversion (supports 1.x and 2.x, Stable Diffision ckpt/safetensors and Diffusers)

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
Step by Step fine-tuning guide: Including BLIP captioning and tagging by DeepDanbooru or WD14 tagger
training LoRA
note.com Image generation
note.com Model conversion

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:

git clone https://github.com/kohya-ss/sd-scripts.git
cd sd-scripts

python -m venv --system-site-packages 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

Answers to accelerate config:

- 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.)

Upgrade

When a new release comes out you can upgrade your repo with the following command:

cd sd-scripts
git pull
.\venv\Scripts\activate
pip install --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. 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: MIT

bitsandbytes: MIT

BLIP: BSD-3-Clause