ai-toolkit is a diffusion model training toolkit designed for fine-tuning image and video generation models. It functions as a containerized model trainer and GPU training job manager, providing the infrastructure to orchestrate dependencies and manage training processes on remote GPU hardware.
The system utilizes low-rank adaptation techniques, including LoRA and LoKr weight optimization, to reduce the hardware requirements for model training. It distinguishes itself through a web-based training controller that allows for the monitoring and modification of hyperparameters, secured by token-based authentication.
The toolkit includes a dataset preparation pipeline that automates image resizing, aspect-ratio bucketing, and the organization of image-text pairs. It also features a multimodal captioning tool that uses vision-language models to automatically generate descriptive text for training datasets.
General model fine-tuning is supported through layer-specific training and pattern-based layer filtering to control which weight groups are updated.
