Analysis updated 2026-05-18
Train a custom character or art style LoRA for the Anima 2B image model
Fine-tune an image model on a low-end GPU with as little as 6GB VRAM
Use the portable edition to train without manually installing Python or dependencies
| thetacursed/anima-trainflow | avbiswas/sam2-mlx | gregowahoo/comfyui-workflow-finder | |
|---|---|---|---|
| Stars | 27 | 27 | 27 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | moderate | easy |
| Complexity | 3/5 | 4/5 | 2/5 |
| Audience | vibe coder | researcher | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
Requires a GPU with at least 6GB VRAM, the portable edition avoids manual Python setup but training still takes time.
Anima TrainFlow is a tool for training a LoRA, short for "Low-Rank Adaptation," a technique for fine-tuning an AI image model on your own custom images without retraining the whole model from scratch, specifically for the Anima 2B image generation model. The goal is to teach the model to recognize and generate a particular character, style, or subject you care about. Everything runs on one page in a simple graphical interface built with Gradio (a Python-based tool for building web UIs). You provide a folder of training images paired with text caption files, set a trigger word (the word you'll type later to activate your custom style), and click Start. The interface shows you live previews of how your LoRA is developing as training runs, so you can see results without waiting until the end. A built-in dataset analyzer automatically works out the best image resolution settings for your training data. The tool is specifically designed to work on hardware with as little as 6GB of GPU memory (VRAM), making it accessible without a high-end graphics card. It comes with a portable edition that bundles everything, including a self-contained Python environment, into a single archive so you don't need to install anything manually. Just extract and run. The project is written in Python and targets Windows, built on top of a modified version of sd-scripts for the Anima 2B architecture.
A simple graphical tool for training a custom LoRA style or character on the Anima 2B image model, even on modest GPUs.
Mainly Python. The stack also includes Python, Gradio.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly vibe coder.
This repo across BitVibe Labs
Verify against the repo before relying on details.