anima-lora-trainer

# Citron Anima LoRA Trainer ## Overview **Citron's Anima LoRA Trainer** (`app.py` = "🍋 Citron's Anima LoRA Trainer") 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 — 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: standard `.safetensors` LoRA usable directly in the **anima-base** ComfyUI workflow. > 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 — they are referenced by `app.py` but pulled from the upstream repo at install time. ## Setup ### Windows Run `CITRON_ANIMA_LORA_TRAINER-V2.bat`. It: 1. Ensures **Git** and **Python 3.10** (via winget if missing). 2. Detects the NVIDIA GPU/driver and picks a matching **PyTorch CUDA wheel** automatically: - Blackwell (RTX 50xx) → cu128, bf16 - Modern (RTX 20/...