# Xora️
This is the official repository for Xora. ## Table of Contents * [Introduction](#introduction) * [Installation](#installation) * [Inference](#inference) * [Inference Code](#inference-code) * [Acknowledgement](#acknowledgement) ## Introduction The performance of Diffusion Transformers is heavily influenced by the number of generated latent pixels (or tokens). In video generation, the token count becomes substantial as the number of frames increases. To address this, we designed a carefully optimized VAE that compresses videos into a smaller number of tokens while utilizing a deeper latent space. This approach enables our model to generate high-quality 768x512 videos at 24 FPS, achieving near real-time speeds. ## Installation # Setup The codebase currently uses Python 3.10.5, CUDA version 12.2, and supports PyTorch >= 2.1.2. ```bash git clone https://github.com/LightricksResearch/xora-core.git cd xora-core # create env python -m venv env source env/bin/activate python -m pip install -e .\[inference-script\] ``` Then, download the model from [Hugging Face](https://huggingface.co/Lightricks/Xora) ```python from huggingface_hub import snapshot_download model_path = 'PATH' # The local directory to save downloaded checkpoint snapshot_download("Lightricks/Xora", local_dir=model_path, local_dir_use_symlinks=False, repo_type='model') ``` ## Inference ### Inference Code To use our model, please follow the inference code in `inference.py` at [https://github.com/LightricksResearch/xora-core/blob/main/inference.py](): For text-to-video generation: ```bash python inference.py --ckpt_dir 'PATH' --prompt "PROMPT" --height HEIGHT --width WIDTH ``` For image-to-video generation: ```python python inference.py --ckpt_dir 'PATH' --prompt "PROMPT" --input_image_path IMAGE_PATH --height HEIGHT --width WIDTH ``` ## Acknowledgement We are grateful for the following awesome projects when implementing Xora: * [DiT](https://github.com/facebookresearch/DiT) and [PixArt-alpha](https://github.com/PixArt-alpha/PixArt-alpha): vision transformers for image generation. [//]: # (## Citation)