anima-lora-trainer

# 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 ### Windows Run `CITRON_ANIMA_LORA_TRAINER-V2.bat`. It: 1. Ensures Git and Python 3.10 are present (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 20/30/40, e...