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Train an image LoRA#

Image LoRAs are trained locally against an image base model and are used in Image Studio like any other LoRA.

  1. Create a project with the image model type and pick the base model from your installed models.
  2. Build a dataset from gallery images. For a style, 30 to 60 varied images; for a subject, 15 to 30 with the subject clearly framed.
  3. Set the run: rank, learning rate, steps, batch size and precision. The defaults suit a 16 GB card; raise the batch size only with more VRAM.
  4. Start. Progress, loss and intermediate checkpoints appear on the run card.

When the run completes the LoRA is registered in the model manager and shows up in the LoRA list of the Generate tab for that base model. Start at weight 0.7 and adjust. See LoRAs.