--- title: LTX Video Fast emoji: 🎥 colorFrom: yellow colorTo: pink sdk: gradio sdk_version: 5.29.1 app_file: app.py pinned: false short_description: ultra-fast video model, LTX 0.9.7 13B distilled --- # LTX Video Fast This project provides an ultra-fast video generation model, LTX 0.9.7 13B distilled. ## Installation 1. **Clone the repository:** ```bash git clone cd ``` 2. **Install the dependencies:** ```bash pip install -r requirements.txt ``` The `requirements.txt` file includes the following dependencies: ``` accelerate transformers sentencepiece pillow numpy torchvision huggingface_hub spaces opencv-python imageio imageio-ffmpeg einops timm av git+https://github.com/huggingface/diffusers.git@main ``` ## Configuration The project uses YAML configuration files to define model parameters and pipeline settings. Example configuration files are located in the `configs` directory. * `configs/ltxv-13b-0.9.7-dev.yaml` * `configs/ltxv-13b-0.9.7-distilled.yaml` * `configs/ltxv-2b-0.9.1.yaml` * `configs/ltxv-2b-0.9.5.yaml` * `configs/ltxv-2b-0.9.6-dev.yaml` * `configs/ltxv-2b-0.9.6-distilled.yaml` * `configs/ltxv-2b-0.9.yaml` To use a specific configuration, you can specify its path when running the generation scripts. ## Usage The project supports different generation modes: text-to-video, image-to-video, and video-to-video. ### Text-to-Video To generate a video from a text prompt, use the `inference.py` script with the `--mode text2video` argument. You must also specify the path to the desired config file using `--config` and a text prompt using `--prompt`. For example: ### Image-to-Video To generate a video from an image, use the `inference.py` script with the `--mode image2video` argument. You must also specify the path to the desired config file using `--config` and the path to the input image using `--image_path`. For example: ### Video-to-Video To generate a video from another video, use the `inference.py` script with the `--mode video2video` argument. You must also specify the path to the desired config file using `--config` and the path to the input video using `--video_path`. For example: Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference