OneTrainer

OneTrainer is a one-stop solution for all your stable diffusion training needs.

It is currently still in very early development. Planned features include:

• Different models: Training on all currently released Stable Diffusion models, this includes the base models (1.x and 2.x), inpainting models and the depth to image model
• Different training methods: Fine-Tuning, LoRA, Embeddings, ControlNet
• VAE fine tuning
• Masked Training: Let the training focus on just certain parts of the samples.

Installation

Installing OneTrainer requires Python 3.10 or newer. Then follow these steps:

• Clone the repository git clone git@github.com:Nerogar/OneTrainer.git
• Navigate into the cloned directory cd OneTrainer
• Set up a virtual environment python -m venv venv
• Activate the new venv venv\scripts\activate
• Install the requirements pip install -r requirements_torch1.txt

Usage

OneTrainer is currently command line only. All commands need to be run inside the active venv created during installation.

All functionality is split into different scrips located in the scripts directory. This currently includes:

• train.py The central training script
• convert_model.py A utility to convert between different model formats
• sample.py A utility to sample any model

To learn more about the different parameters, execute <scipt-name> -h. For example scripts\train.py -h