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Open-Sora - AI Video Models Tool

Overview

Open-Sora is an open-source toolkit and model collection for efficient AI video generation maintained in the hpcaitech/Open-Sora GitHub repository. The project bundles training and inference code, example scripts and notebooks, and model checkpoints intended to make research and prototyping in text-to-video and related video synthesis tasks reproducible and easier to run. According to the GitHub repository, Open-Sora focuses on efficiency—providing memory- and compute-conscious pipelines (mixed precision, checkpointing, and multi-GPU support) aimed at shortening iteration time and enabling higher-resolution outputs on commodity hardware. Open-Sora is positioned for researchers and engineers who need a practical, extensible base for experimenting with video generative models and for integrating video synthesis into downstream applications. The repo includes example pipelines for data preparation, model training, sampling, and evaluation so teams can reproduce published results or adapt components (models, schedulers, and samplers) to custom datasets. For the most up-to-date capabilities, model releases, and usage examples, consult the project's GitHub page.

Installation

Install via docker:

git clone https://github.com/hpcaitech/Open-Sora.git
cd Open-Sora && docker build -t open-sora .
docker run --gpus all -it --rm -v $(pwd):/workspace open-sora bash

Key Features

  • Open-source model checkpoints and training code for AI video generation (hosted in the repository).
  • Inference pipelines designed for efficiency: mixed-precision and memory-friendly sampling strategies.
  • Multi-GPU and distributed training support for larger scale experiments and faster training.
  • Example scripts and Jupyter notebooks for data prep, training, sampling, and evaluation.
  • CLI and Python integration points for embedding generation into custom workflows and apps.

Community

Open-Sora is hosted on GitHub under hpcaitech/Open-Sora; the repository centralizes issues, pull requests, and release artifacts. The project attracts researchers and engineers contributing code, bug reports, and usage questions. For current activity (stars, open issues, recent commits, and discussions) and model release notes, check the repository directly; the README and issues page are the primary places for updates and community-driven support.

Last Refreshed: 2026-01-09

Key Information

  • Category: Video Models
  • Type: AI Video Models Tool
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