IC LoRA enables conditioning video generation on reference video frames at inference time, allowing fine-grained video-to-video control on top of a text-to-video, base model. It allows also the usage of an intial image for image-to-video, and generate audio-visual output.

Model Files

ltx-2-19b-ic-lora-canny-control.safetensors

License

See the LTX-2-community-license for full terms.

Model Details

Base Model: LTX-2-19b Video
Training Type: IC LoRA
Control Type: Canny edge conditioning

🔌 Using in ComfyUI

Copy the LoRA weights into models/loras.
Use the official IC-LoRA workflow from the LTX-2 ComfyUI repository.

Dataset

The model was trained using the Lightricks/Canny-Control-Dataset.

Citation

bibtex

@article{hacohen2025ltx2,
  title={LTX-2: Efficient Joint Audio-Visual Foundation Model},
  author={HaCohen, Yoav and Brazowski, Benny and Chiprut, Nisan and Bitterman, Yaki and Kvochko, Andrew and Berkowitz, Avishai and Shalem, Daniel and Lifschitz, Daphna and Moshe, Dudu and Porat, Eitan and others},
  journal={arXiv preprint arXiv:2601.03233},
  year={2025}
}

Acknowledgments

Base model by Lightricks
Training infrastructure: LTX-2 Community Trainer

Lightricks/LTX-2-19b-IC-LoRA-Canny-Control

LTX-2 19B IC-LoRA Canny Control

What is In-Context LoRA (IC LoRA)?