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anima-lora-trainer

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Train a custom anime LoRA on the ANIMA base model with Citron's local Gradio trainer (kohya sd-scripts), <6GB VRAM, character/style LoRAs; covers setup, dataset prep, training params, and using the result in the anima-base workflow

plugin/skills/anima-lora-trainer/SKILL.md

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Nov 9, 2026
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# Citron Anima LoRA Trainer

## Overview

Citron's Anima LoRA Trainer (`app.py`, titled "Citron's Anima LoRA Trainer" in the UI) is a local Gradio UI for training LoRA adapters on the Anima diffusion model using kohya-ss/sd-scripts. It trains on ~6GB VRAM with the default settings, the same low-VRAM profile as Anima generation.

- Created by Citron Legacy; UI repo: `https://github.com/citronlegacy/citron-anima-lora-trainer-ui`. The Aitrepreneur adaptive installers clone the fork `https://github.com/aitrepreneur/citron-anima-lora-trainer-ui`.
- Training backend: `kohya-ss/sd-scripts` (`https://github.com/kohya-ss/sd-scripts`), launched via `accelerate launch`.
- Trains LoRAs for Anima DiT (Cosmos-2B). Uses Anima's own components: DiT weights + Qwen3-0.6B text encoder + Qwen-Image VAE.
- Output: a standard `.safetensors` LoRA usable directly in the anima-base ComfyUI workflow.

> The network module is `networks.lora_anima` and the training script is `sd-scripts/anima_train_network.py` (an Anima-specific kohya script the installer expects). Confirm these exist after the installer's `git clone` of sd-scripts. `app.py` references them, but they are pulled from the upstream repo at install time.

## Setup
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