Stable Diffusion LoRA Training Pipeline

Orchestrates LoRA fine-tuning for Stable Diffusion XL using the diffusers library and Kohya ss-scripts. Manages dataset preparation with BLIP-2 auto-captioning, configures AdaFactor optimizer parameters, and exports safetensors checkpoints with A1111 metadata embedding.

Installation

Use the upstream install or setup path that matches your environment:

• git clone https://github.com/kohya-ss/sd-scripts.git
• pip install torch==2.6.0 torchvision==0.21.0 --index-url https://download.pytorch.org/whl/cu124
• pip install --upgrade -r requirements.txt
• This installation is for CUDA 12.4. If you use a different version of CUDA, please install the appropriate version of PyTorch. For example, if you use CUDA 12.1, please install pip install torch==2.6.0 torchvision==0....

Requirements and caveats from upstream:

• Python 3.10.x and Git:
• Python 3.10.x: Download Windows installer (64-bit) from https://www.python.org/downloads/windows/
• Python 3.11.x, and 3.12.x will work but not tested.

Basic usage or getting-started notes:

• Open a regular Powershell terminal and type the following inside:

• powershell

• cd sd-scripts

• Source: https://github.com/kohya-ss/sd-scripts

• Extracted from upstream docs: https://raw.githubusercontent.com/kohya-ss/sd-scripts/HEAD/README.md

Source

• Agent Skill Exchange