anima-lora-trainer

1# Citron Anima LoRA Trainer
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3## Overview
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5Citron'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.
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7- 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`.
8- Training backend: `kohya-ss/sd-scripts` (`https://github.com/kohya-ss/sd-scripts`), launched via `accelerate launch`.
9- Trains LoRAs for Anima DiT (Cosmos-2B). Uses Anima's own components: DiT weights + Qwen3-0.6B text encoder + Qwen-Image VAE.
10- Output: a standard `.safetensors` LoRA usable directly in the anima-base ComfyUI workflow.
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12> 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.
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14## Setup
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16### Windows
17Run `CITRON_ANIMA_LORA_TRAINER-V2.bat`. It:
181. Ensures Git and Python 3.10 are present (via winget if missing).
192. Detects the NVIDIA GPU/driver and picks a matching PyTorch CUDA wheel automatically:
20   - Blackwell (RTX 50xx) → cu128, bf16
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