metadata

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

Clone the repository:

git clone <repository_url>
cd <repository_directory>

Install the dependencies:
```
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