# 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**.

In the left **LoRA Controller** panel, pick the **Training Model**:

- **Flux LoRA** — requires a trigger word.
- **Z-Image Turbo** — trigger word optional.
- **Z-Image Turbo V2** — trigger word optional.

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. For Flux it's required; for Z-Image models it's an On/Off toggle.

## 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](/docs/product/projects-media).

## 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. Click **Generate Captions** in the left panel (or **Auto Caption** from an image's caption dialog).

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**.

Choose a captioning model (Gemini 2.5 Flash, GPT-5 Mini, Claude Sonnet, or GPT-5). 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.

## Auto-Caption (Z-Image Training)

Z-Image captioning is built around a **Training Focus** (set in the left panel):

- **Style** — captions describe *what* is depicted, not the visual style.
- **Content** — captions describe context/variations, not fixed identity (use a trigger word; for content you also pick **Person** or **Object**).
- **Balanced** — captions describe both content and style.

Z-Image supports two **Caption Modes**:

- **Single** — one master caption applied to all images.
- **Per Image** — an individual caption per image.

Captions are optional for Z-Image. If a trigger word is enabled, it's prepended to generated captions. Use the same **Generate Captions** button; choose a captioning model and cost applies per image.

## 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.
- Z-Image models expose extra options (e.g. learning rate) under the **Training Parameters** section.

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](/docs/product/chat-image-gen)):

1. Open the **LoRA Models** selector and click **Add LoRA** (the **+** / 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: trigger words for Z-Image content LoRAs control *when* your subject appears; without one the subject may bleed into every generation. Style/object type also affects how the trigger is phrased in the prompt.