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 .safetensors file
• 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! 🎉