{"slug": "one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards", "title": "one character, every tab: training a local LoRA that changes clothes, on 8 GB cards and on a Mac", "summary": "A developer behind Locally Uncensored, an open-source AGPL-3.0 desktop app for running AI models locally with 180,000+ downloads, shipped version 3.0.7 with a reworked Character Studio that trains Z Image character LoRAs on-device. The release adds per-photo caption fields, a Low VRAM training mode targeting cards from about 8 GB (down from 12 GB), and macOS training that takes roughly two hours for 1,200 steps on an M5 Pro. The developer notes that Low VRAM, per-photo captions, frame-based character extraction and the Edit reference row have run only in automated tests, and that 8 GB cards were estimated from the trainer's figures rather than measured.", "body_md": "Locally Uncensored is an open source desktop app (AGPL-3.0) that runs AI models on your own machine: chat, an agent, image and video generation. It has 180,000+ downloads. For 3.0.7 I wanted a character you train once to work everywhere in the app, and I wanted more machines to be able to train one.\n\nThis post follows one character from training to image, edit, video and chat. It also says where my testing stopped, which for this feature is further back than I would like.\n\nLocal characters use the Z Image family. You drop photos of one person or character into Character Studio, pick a trigger word and train on your own machine. Three things are new in 3.0.7.\n\nThe Train tab has a short text field under each photo, on Windows, Linux and Mac. You write there what changes from photo to photo: clothes, hair, place. That text goes into the photo's caption after the trigger word. The trained character then keeps its face and body without being tied to the one outfit it wore in most photos. An empty field keeps the caption as it was.\n\nDescribe photos fills the empty fields for you with the local chat model picked in Chat, if that model can see images. It never sends the photos to a cloud model. The per photo text has run in automated tests only.\n\nOn Windows and Linux, training now has a second setting next to the training length:\n\n```\nNormal     the 12 GB recipe as before\nLow VRAM   512 px instead of 768 px\n           28 of the model's 30 blocks in system memory\n           saved activations in system memory\n           LoRA rank 16 instead of 32\n```\n\nEach step takes clearly longer, and fine detail comes out softer. A card with less than 11 GB is pointed at Low VRAM, both in the tab and in the trainer's own check.\n\nLow VRAM lets cards from about 8 GB train. That number is worked out from the trainer's own figures. I have not measured it on an 8 GB card. Low VRAM as a whole has run in automated tests only so far.\n\nOn a Mac, Character Studio's Train tab now trains a Z Image character from 4 to 100 photos with the Mac's image engine. The first run downloads a training adapter of 340 MB, and the result goes into the Mac's LoRA folder.\n\nIt is slow:\n\n```\nM5 Pro, one step        about 7 seconds\nStandard (1200 steps)   a little over two hours\n```\n\nMy own run was 10 photos and 100 steps on one Mac with 48 GB. The Standard and Thorough settings, Macs with less memory and stopping a training in the middle have not run yet. This is on macOS only.\n\nThe lightbox and the large view of a video offer Use frames for a character. LU takes frames spread evenly over the clip:\n\n```\ndefault    8 frames\nslider     4 to 20 frames\n```\n\nYou untick the frames that do not show the figure, then train with the rest or save them as a character. On a Mac this feeds the same Mac training. This has run in automated tests only.\n\nWhen Create runs on ComfyUI, Image and Edit have a character chip next to the model chip. Pick a character there and its LoRA and trigger word go into the run.\n\nThe pick also sets the model. Before, picking a character left the image model as it was, and on a model of another family the run left the character out. Now the pick sets an installed Z Image model. Where none fits, the line under the character says so with a button to switch, and Create does not start a run that would ignore the character. The same line tells you to describe the key features in the prompt too, because the trigger word alone often does not hold the look (issue 161).\n\nTwo limits in Edit:\n\n```\nEdit with a mask     does not take a character\nTrained characters   up to 3 of the training photos as references, at most 1024 px each\n```\n\nThe Trained characters row sits in the reference strip of Edit. A character trained before 3.0.7 has no photos there, and I have not tried the row with a real training set yet.\n\nA character video is two runs. LU first makes a picture of the character, then starts the clip from that picture:\n\n```\nStep 1 of 2    picture of the character\nStep 2 of 2    clip from that picture\n```\n\nThis works on Video, Animate, Extend, Multishot, MiniMax H3, Motion Control and Talking Character. A start image of your own wins over the character picture. A video model that only takes text, or a tab with no video model installed, says so before anything runs, so you do not wait through step 1 for nothing.\n\nI checked this in the app on Windows with a stand-in character, not a real trained one. How well a real character keeps its face has not been checked, and step 2 has not run with a real video model yet.\n\nThe image and video tools in the chat take a character by name or by trigger word.\n\nCharacter Studio's Use tab on a Mac lists the characters in the Mac's LoRA folder, including the ones the Mac trained itself. A pick brings the Z Image model the character was trained for, and Image, the video tabs and the chat tools take the character as they do on Windows. A video starts from a picture of the character made on the Mac.\n\nThe Mac parts of 3.0.7 have run in automated tests and with the real engine on one Mac with 48 GB, but have not been clicked through in a built app yet.\n\nIf you trained a character on LU Cloud, the cloud character shelf has Use locally. It saves a Z Image character into the LoRA folder of this machine, so the local Use character shelf lists it next to your own.\n\n```\nfile of that name already there    LU stops and says so, nothing is replaced\nother model families               refused, with the reason\n```\n\nThis has run in automated tests only, not yet against the real service.\n\nA character trained on this machine can be deleted from the Use character shelf. LU asks first, and the file goes to the Recycle Bin or Trash.\n\n```\nreal trained character in the app       not checked, stand-in LoRA only\nstep 2 of a character video             not run with a real video model\nper photo text (changing clothes)       automated tests only\nLow VRAM                                automated tests only, not measured on 8 GB\ntraining on a Mac                       10 photos, 100 steps, one Mac with 48 GB\nStandard and Thorough on a Mac          not run\nUse frames for a character              automated tests only\nTrained characters row in Edit          not with a real training set\nUse locally from LU Cloud               automated tests only\n```\n\nThe real app check ran on one Windows machine with an NVIDIA card. If you try any of these on your own hardware, a report on the issue tracker helps more than another run on mine. A Low VRAM run on an 8 GB card is the one I would most like to see.\n\nIn 3.0.7 a local character can change clothes between photos, train on cards from about 8 GB with Low VRAM (worked out, not measured), and train on a Mac, slowly. Once trained, it works in Image and Edit through a chip next to the model, in every video tab as Step 1 of 2 and Step 2 of 2, and in the chat by name or trigger word. The video step has not run with a real video model yet, and the face check with a real character is still open.\n\nThe code is at [github.com/PurpleDoubleD/locally-uncensored](https://github.com/PurpleDoubleD/locally-uncensored), and the [Character Studio chapter of the handbook](https://locallyuncensored.com/guide/character-studio/) covers photos and training. Downloads are on [locallyuncensored.com](https://locallyuncensored.com/).\n\n*AI-assisted: I wrote this with help from an AI model and checked the facts against the code and the changelog.*", "url": "https://wpnews.pro/news/one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards", "canonical_source": "https://dev.to/purpledoubled/one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards-and-on-a-mac-3gl3", "published_at": "2026-10-20 15:13:15+00:00", "updated_at": "2026-10-20 15:19:30.428595+00:00", "lang": "en", "topics": ["ai-tools", "generative-ai", "ai-products", "machine-learning"], "entities": ["Locally Uncensored", "Character Studio", "Z Image", "ComfyUI", "Apple M5 Pro", "macOS"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards", "markdown": "https://wpnews.pro/news/one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards.md", "text": "https://wpnews.pro/news/one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards.txt", "jsonld": "https://wpnews.pro/news/one-character-every-tab-training-a-local-lora-that-changes-clothes-on-8-gb-cards.jsonld"}}