On-device Sora
O
On Device Sora
Overview :
On-device Sora is an open-source project aimed at enabling efficient video generation on mobile devices (such as the iPhone 15 Pro) using technologies like Linear Proportional Jump (LPL), Time Dimension Tag Merging (TDTM), and Concurrent Inference with Dynamic Loading (CI-DL). Developed from the Open-Sora model, it generates high-quality videos based on text input. Its main advantages include efficiency, low power consumption, and optimization for mobile devices. This technology is applicable in scenarios that require rapid video creation on mobile devices, such as short video production and advertising. The project is currently open source and can be used free of charge.
Target Users :
This product is designed for creators, advertisers, and content developers who need to quickly generate video content on mobile devices. It enables users to efficiently produce high-quality videos without relying on cloud computing, making it especially suitable for users who need to create content rapidly in mobile scenarios.
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Use Cases
Creators can quickly generate short video content on mobile devices using this model.
Advertisers can create video ads on mobile devices based on advertising copy.
Content developers can leverage this model to generate dynamic video assets for mobile applications.
Features
Supports text-to-video generation, able to produce high-quality videos based on input text.
Optimized for mobile device performance, suitable for devices like the iPhone 15 Pro.
Utilizes Linear Proportional Jump (LPL) technology to enhance generation efficiency.
Supports Time Dimension Tag Merging (TDTM) to reduce computational resource consumption.
Provides Concurrent Inference with Dynamic Loading (CI-DL) to improve runtime speed.
How to Use
1. Clone the project repository to your local machine.
2. Install the necessary dependencies (such as Python 3.10 and related libraries).
3. Convert the model to MLPackage format (supporting T5, STDiT, and VAE).
4. Open the project in Xcode and configure your Apple developer account.
5. Run the application on an iPhone 15 Pro or later device.
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