# Open-Sora-Plan — Open-Source Video Generation Framework

> A community-driven project to reproduce Sora-class text-to-video capabilities with open-source models and training code.

## Install

Save in your project root:

# Open-Sora-Plan — Open-Source Video Generation Framework

## Quick Use
```bash
git clone https://github.com/PKU-YuanGroup/Open-Sora-Plan.git
cd Open-Sora-Plan
pip install -e .
python scripts/inference.py --prompt "A cat walking on a beach" --ckpt_path model.safetensors
```

## Introduction
Open-Sora-Plan is a community-driven effort to build an open-source text-to-video generation system comparable to commercial offerings. It provides training pipelines, model architectures, and pre-trained checkpoints for generating video from text prompts.

## What Open-Sora-Plan Does
- Generates video clips from text descriptions
- Supports variable resolution and duration settings
- Provides end-to-end training scripts for custom datasets
- Includes a 3D VAE for temporal video compression
- Offers progressive training from images to video

## Architecture Overview
The system combines a CausalVideo VAE that compresses video into a compact latent space with a Diffusion Transformer (DiT) that denoises latent representations conditioned on text embeddings. The VAE handles spatial and temporal compression jointly, while the DiT uses 3D attention to model motion across frames.

## Self-Hosting & Configuration
- Requires Python 3.10+ and PyTorch 2.x with CUDA
- Multi-GPU setup recommended for training (8x A100 or equivalent)
- Inference runs on a single GPU with at least 16 GB VRAM
- Configure video resolution and frame count via YAML config files
- Pre-trained checkpoints available on Hugging Face

## Key Features
- Fully open-source training and inference code
- Scalable architecture from 256p to 720p resolution
- CausalVideo VAE with strong temporal consistency
- Text conditioning via pre-trained language model encoders
- Active community with frequent model updates

## Comparison with Similar Tools
- **Open-Sora** — HPC-AI Tech's implementation; Open-Sora-Plan uses a different VAE approach
- **Wan2.1** — Alibaba's model with broader language support
- **CogVideo** — Tsinghua's system with stronger prompt adherence at lower resolutions
- **AnimateDiff** — motion module for image diffusion; Open-Sora-Plan is end-to-end

## FAQ
**Q: Can I fine-tune on my own video data?**
A: Yes, training scripts accept custom datasets with text-video pairs.

**Q: What video lengths can it produce?**
A: Current checkpoints support up to several seconds; longer clips require interpolation.

**Q: How does quality compare to commercial Sora?**
A: Quality is advancing rapidly but commercial systems still lead on coherence and length.

**Q: Is commercial use permitted?**
A: Check the model license — most checkpoints use Apache 2.0.

## Sources
- https://github.com/PKU-YuanGroup/Open-Sora-Plan
- https://pku-yuangroup.github.io/Open-Sora-Plan/

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Source: https://tokrepo.com/en/workflows/asset-d706f66e
Author: AI Open Source