FLUX is great at generating images, but locking in a specific aesthetic or character is easier with a  LoRA. Here's how to create your own.

Key Inputs

Load Images from Folder: Paste path to folder containing your image dataset, if you uploaded or are accessing it from your Floyo inputs folder, the input path would look like "input/#input/your_dataset_folder_name"

Flux LoRa Trainer - Trigger Word: Add a trigger word that you will use in your prompts when applying the LoRa in image generation

Quick start recipe

• Upload a Zip file of curated images + captions.

• Enable is_style and include a unique trigger phrase.

• Compare checkpoints with a range of steps to find the sweet spot.

Prepping your dataset

• Fewer, ultra‑high‑res (≈1024×1024+) images beat many low‑quality ones.

• Every image must clearly represent the style or individual and be artifact‑free.

• For people, aim for at least 10-20 images in different background (5 headshots, 5 wholebody, 5 halfbody, 5 in other scene)

Captioning

• Give the style a unique trigger phrase (so as not be confused with a regular word or term).

• For better prompt control, add custom captions that describe content only—leave style cues to the trigger phrase. Create accompanying .txt files with the same name as the image its describing.

• If you do add custom captions, be sure to turn on is_style to skip auto‑captioning. It is set to off by default.

Training steps

• The default is set to around 2000, but you can train multiple checkpoints (e.g., 500, 1000, 1500, 2000) and pick the one that balances style fidelity with prompt responsiveness.

• Too few steps: the character becomes less realistic or the style fades.

• Too many steps: model overfits and stops obeying prompts.

Output Path

• Will be a URL in the Preview Text Node.