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Team

Shared LoRAs

Train one in a team workspace and it belongs to the team, usable by everyone and absent from every personal library including yours.

Train a LoRA while working in a team workspace and it belongs to the organisation. Every member can see it and generate with it, from any board in that workspace, without anybody sharing anything.

It is how a trained look becomes house style without anybody having to distribute a file.

Trained in Belongs to Appears in
A team workspace The organisation The team library, for every member
Your personal workspace You Your personal library only

A team LoRA appears in no personal library at all, including the library of the person who trained it. It is not copied to the team and kept privately as well.

A written brand guideline describes a look and depends on everyone reading it, interpreting it the same way, and remembering it under deadline.

A shared LoRA produces the look. A new member generates on-brand on their first afternoon without having read anything, because the adapter carries what the document would have described.

That is worth building deliberately:

  • A product LoRA per thing you make repeatedly, so it is recognisably itself across every campaign
  • A house style LoRA trained on work that already went out, so new work matches the back catalogue
  • A 3D style LoRA trained on ten to twenty of your own textured models, so generated geometry arrives in your visual language

Exactly like using your own. Pick it in lora-generate, set its scale, and put its trigger word in the prompt.

The trigger is the one thing that has to travel by word of mouth, so keep the LoRA’s name and its trigger obviously related. A team LoRA named “Aurora chair” with a trigger nobody can guess is a LoRA nobody uses.

Run the product LoRA high and the house style LoRA low, and your object arrives rendered the way your studio renders things.

The one hard constraint is generational. FLUX.1 and FLUX.2 adapters run through different endpoints and cannot be combined in a single run, so if you intend to stack, train both halves on the same generation.