This package provides tools and scripts for training and fine-tuning Lightricks' LTX-2 audio-video generation model. It enables LoRA training, full fine-tuning, and training of video-to-video transformations (IC-LoRA) on custom datasets.
All detailed guides and technical documentation are in the docs directory:
- ⚡ Quick Start Guide
- 🎬 Dataset Preparation
- 🛠️ Training Modes
- ⚙️ Configuration Reference
- 🚀 Training Guide
- 🧪 Inference Guide
- 🔧 Utility Scripts
- 📚 LTX-Core Documentation
- 🛡️ Troubleshooting Guide
- LTX-2 Model Checkpoint - Local
.safetensorsfile - Gemma Text Encoder - Local Gemma model directory (required for LTX-2)
- Linux with CUDA - CUDA 13+ recommended for optimal performance
- Nvidia GPU with 80GB+ VRAM - Recommended for the standard config. For GPUs with 32GB VRAM (e.g., RTX 5090), use the low VRAM config which enables INT8 quantization and other memory optimizations
We welcome contributions from the community! Here's how you can help:
- Share Your Work: If you've trained interesting LoRAs or achieved cool results, please share them with the community.
- Report Issues: Found a bug or have a suggestion? Open an issue on GitHub.
- Submit PRs: Help improve the codebase with bug fixes or general improvements.
- Feature Requests: Have ideas for new features? Let us know through GitHub issues.
Have questions, want to share your results, or need real-time help?
Join our community Discord server to connect with other users and the development team!
- Get troubleshooting help
- Share your training results and workflows
- Collaborate on new ideas and features
- Stay up to date with announcements and updates
We look forward to seeing you there!
Happy training! 🎉