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