Step-Video-T2V
by Leapfrogging StarStep-Video-T2V is an open-source text-to-video model developed by Leapfrogging Star, featuring 30 billion parameters and capable of generating high-quality videos up to 204 frames long. The model uses a deeply compressed variational autoencoder (Video-VAE) for efficient training and inference, supporting bilingual text inputs in Chinese and English. It employs a diffusion-based Transformer (DiT) architecture with a 3D full-attention mechanism, optimized for generating videos with strong motion dynamics and high aesthetic quality.
What is Step-Video-T2V?
Step-Video-T2V is an open-source text-to-video model developed by Leapfrogging Star, designed to generate high-quality videos from text prompts. With 30 billion parameters, it supports videos up to 204 frames long and uses a deeply compressed variational autoencoder (Video-VAE) for efficient training and inference.
Key Features
- High-Quality Video Generation: Produces videos with strong motion dynamics and high aesthetic quality.
- Bilingual Support: Accepts Chinese and English text prompts.
- Efficient Architecture: Built on a diffusion-based Transformer (DiT) with 3D full-attention.
- Direct Preference Optimization (DPO): Enhances video quality by fine-tuning with human preference data.
Technical Details
- Video-VAE: Achieves 16x16 spatial and 8x temporal compression for efficient processing.
- DiT Architecture: Uses Flow Matching training to denoise input into latent frames.
- System Optimization: Includes tensor parallelism, sequence parallelism, and Zero1 optimization for distributed training.
Use Cases
- Video Content Creation: Quickly generates creative videos from text.
- Advertising: Produces personalized ad content.
- Education: Creates educational videos for better knowledge retention.
- Film and Entertainment: Assists in generating special effects and animations.
- Social Media: Enables personalized video generation for social platforms.
Getting Started
Visit the GitHub repository to access the model and documentation.
Model Capabilities
Model Type
multimodal
Supported Tasks
Text-To-Video Generation
Video Content Creation
Ad Production
Educational Video Generation
Film And Entertainment
Tags
Text-to-Video
AI Model
Open Source
Video Generation
Bilingual Support
Deep Learning
Diffusion Models
Transformer Architecture
Video Content Creation
High-Quality Video
Usage & Integration
Pricing
free
License
Open Source
MIT
Screenshots & Images
Additional Images
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