Anima TrainFlow is a streamlined, one-page GUI for training LoRA on the Anima 2B model. Optimized to run on hardware with as little as 6GB of VRAM, it eliminates technical overhead by focusing on the essential settings that impact training results the most.
- Download Portable Version (1.7GB)
- Extract the archive using 7-Zip or WinRAR.
- Run
start_trainer.bat. - Open the
🔧 Paths to Models <- Set Onceaccordion and specify the paths to your model files. - Specify your Dataset Path (images + .txt files) and Trigger Word, then click Start.
If you prefer to set up the environment manually instead of using the portable version, follow these steps:
- Clone the repository:
git clone https://github.com/ThetaCursed/Anima-TrainFlow cd Anima-TrainFlow - Install dependencies:
Install_Requirements.bat - Launch the Trainer:
start_trainer.bat
- Zero-Tab Interface: All critical parameters (Trigger Word, Rank, LR, Steps) are accessible on a single screen.
- Live Training Previews Watch your LoRA improve in real-time. The built-in gallery automatically updates whenever a new sample is generated.
- Smart Dataset Analyzer: Automatically calculates optimal base resolution and bucket sizes.
- Portable Edition: Includes an embedded Python environment to avoid installation or complex setup.
- Low VRAM Friendly: Specifically tuned for 6GB+ NVIDIA GPUs.
- Optimized Defaults: Pre-configured for BF16 precision and latent caching to ensure maximum performance and stability.
- Prodigy Native: Intelligent Learning Rate handling and optimized defaults for the Prodigy optimizer.
Place all your training images (.png, .jpg, .webp) in a single folder. Every image must have a matching text file with the same name containing its tags/captions (e.g., image1.png and image1.txt).
- OS: Windows 10/11.
- GPU: NVIDIA GPU (6GB+ VRAM recommended for Anima 2B training).
- Storage: ~5GB of free space (SSD recommended).
- Core: Based on a modified version of
sd-scriptsfor Anima 2B architecture. - UI: Built with Gradio featuring a customized dark theme.
- Backend: Utilizes
accelerate launchfor optimized execution. - Auto-Save: All paths and configurations are automatically saved to
settings.json.
