Training & Using LoRAs

Train a custom AI model on your own images, then call it in generations with a trigger word. LoRA training lives in the dashboard; applying a LoRA happens in the chat bar.

Create a LoRA Model

To start a new LoRA:

  1. Open the LoRA Training screen in the dashboard.
  2. Click Create New LoRA (or the Menu button at the top of the center panel, then New).
  3. Enter a descriptive name (e.g. "My Custom Style") and press Enter or click Create.

Flux LoRA is the training model. It requires a trigger word. The Training Model selector only appears when there is more than one model to pick, so today it is hidden — Z-Image training is switched off, and this page describes the Flux flow only. LoRAs you trained on Z-Image before it was switched off still open, still show their settings, and still work in generations.

Set a Trigger Word (the word you'll type in prompts to activate the LoRA). Click the wand icon next to the field to generate a random one.

Collect & Organize Training Images

The center panel holds your training set; the right Image Library panel is your source.

To add images:

  • Click images in the right Image Library to add them. Shift+click adds a range. Filter the library by AI Generated, Rendered, Upscaled, or Uploaded badges, or use the search box.
  • Click the empty drop area or the Add More tile to upload files or pick from your library.
  • Paste with Ctrl+V — from the clipboard, from a copied canvas image node, or from the Framo Chrome extension.

Remove an image with the X on its tile. Use Clear All (top right) to empty the set. Recommended count is 15–25 images (minimum 10, maximum 30).

Pointer: training images come from the same library as your generated/uploaded images across Framo, so anything you make on the canvas can be reused here. See Projects, media library & stock.

Crop Non-Square Images

Training needs square (1:1) images. Non-square images are center-cropped to 1:1 automatically, but you can adjust the crop.

To crop: click an image tile (or its Crop button, bottom-left — amber when an image is non-square). In the Image Crop Dialog, drag to reposition the 1:1 crop, then save. The dialog can also AI Extend a non-square image to 1:1 or Remove Watermark (both cost credits); accept the result to replace the image in your set.

Auto-Caption (Flux Training)

Good captions describe everything except what the LoRA should learn — the caption acts like a subtraction: whatever you describe becomes interchangeable at generation time, whatever you leave unsaid binds to the trigger word as the learned style. Click Auto Caption in the left panel; the dialog's own button reads Caption All N Images.

For Flux, pick a caption category describing what the model learns implicitly:

  • Design Language — shape, form, proportions, silhouette.
  • CMF — color, material, finish.
  • Light & Mood — lighting, atmosphere, post-processing.
  • Artistic Medium.

Captioning always runs on Claude Opus — there is no per-run model choice to make. Auto-captioning costs credits per image; Skip existing avoids re-captioning images that already have a caption. You can edit any caption by clicking the message icon on its tile.

Trigger-word position

Where the trigger word sits in the caption changes how the style is applied — and you should prompt the same way you captioned:

  • Head (In the style of <trigger>, <description>) — for detail-rich, multi-part subjects (interiors, complex products, vehicles). The trigger sets the style before each part (dashboard, seats, console…) is described, so each one is style-conditioned as it's built.
  • Tail (<description>, in the style of <trigger>) — for simpler, holistic subjects (exteriors, painterly styles) where there aren't many discrete parts to condition.

Pointer: for the deeper method — captioning as subtraction, training one car class to generate another, and divergent vs convergent datasets — see Training a design LoRA — the method.

Configure Training Parameters

In the left LoRA Controller:

  • Training Steps — drag the slider or type a value. A Recommended range (about 30–50× your image count) shows below; click Apply to use it. More steps = better quality but longer training.

A Training Status Summary shows whether Name, Trigger, Images, Captions, and Steps each meet requirements (green = ready, red = missing).

Submit a Training Job

When everything is green, click Start Training at the bottom of the left panel. The button shows the estimated credit cost. Confirm you have a name, a valid trigger word (where required), 10–30 images, and captions where required.

Track Training Progress / Status

Once submitted, the left panel shows a live Training Progress bar with status: In queue (with position), Training in progress, or Processing results, plus the latest log line and a percentage.

A model's status is shown as a banner: Draft (editable), Queued, Training, Successfully Trained (read-only), or Training Failed (read-only). Only Draft models can be edited; submitted/completed models open read-only.

Browse Completed LoRAs & Manage Drafts

Open the Menu button at the top of the center panel:

  • Open — lists your models split into WIP (preparing/queued/training/processing) and Completed. Pick one to load its images, captions, and settings.
  • Save — saves the current draft (images, captions, crops, settings also auto-save).
  • Load Dataset — copy the image set + captions from another of your models into the active draft.
  • Delete — permanently removes the model and its training data.

From the empty-state screen you can also use Create New LoRA or Open Existing LoRA.

Apply a LoRA in Generation (Trigger Word)

To use a finished LoRA in a generation, go to the chat bar / generation controls (see Chat bar: generating images):

  1. Open the LoRA bubble in the chat bar's input row and use its + to open the LoRA browser.
  2. Pick from your own completed LoRAs or community LoRAs. Up to 4 LoRAs can be combined.
  3. Each selected LoRA shows its Trigger word (copy it with the copy icon) and a Scale control. The slider covers the comfortable range; type a higher value (up to the API max of 4) to over-push. A Total Strength indicator warns when the combined scale gets high.
  4. Put the trigger word in your prompt to activate the LoRA. When a LoRA with a trigger word is added, Framo can auto-insert the trigger phrasing (e.g. "in the style of <trigger>") for you.

Pointer: the trigger word controls when your learned style appears; a LoRA applied without it may bleed into every generation. Where the word sits in the prompt should match where it sat in the captions — see Trigger-word position above.