OneTrainer

Del README

• Model formats: diffusers and ckpt models
• Training methods: Full fine-tuning, LoRA, embeddings
• Masked Training: Let the training focus on just certain parts of the samples
• Automatic backups: Fully back up your training progress regularly during training. This includes all information to seamlessly continue training
• Image augmentation: Apply random transforms such as rotation, brightness, contrast or saturation to each image sample to quickly create a more diverse dataset
• TensorBoard: A simple TensorBoard integration to track the training progress

Extractos del README del proyecto sobre GitHub. Los derechos de autor y las licencias permanecen con los respectivos autores.