Wan2.1-I2V-14B-480P
| Property | Value |
|---|---|
| Model Size | 14B parameters |
| Resolution | 480P |
| License | Apache 2.0 |
| Architecture | Diffusion Transformer with T5 Encoder |
| Model Dimension | 5120 |
| Number of Heads | 40 |
| Number of Layers | 40 |
What is Wan2.1-I2V-14B-480P?
Wan2.1-I2V-14B-480P is a state-of-the-art image-to-video generation model that represents part of the Wan2.1 suite of video foundation models. This specific model is optimized for generating 480P resolution videos from input images, utilizing a sophisticated architecture that combines a novel 3D causal VAE with advanced diffusion transformer technology.
Implementation Details
The model is built on a Diffusion Transformer architecture with a T5 Encoder for text processing. It features 5120 dimensional embeddings, 40 attention heads, and 40 transformer layers. The implementation includes cross-attention mechanisms in each transformer block and employs a specialized MLP for processing time embeddings.
- Advanced VAE architecture (Wan-VAE) for efficient video processing
- Flow Matching framework within the Diffusion Transformer paradigm
- Shared MLP across transformer blocks with individual bias learning
- Optimized for 480P video generation with maintained temporal consistency
Core Capabilities
- High-quality image-to-video conversion at 480P resolution
- Support for both single and multi-GPU inference
- Efficient memory usage and processing speed
- Compatible with prompt extension capabilities
- Integration with popular frameworks like Gradio and Diffusers
Frequently Asked Questions
Q: What makes this model unique?
The model combines state-of-the-art performance with practical efficiency, particularly in its ability to generate high-quality 480P videos while maintaining reasonable computational requirements. Its novel Wan-VAE architecture and specialized training approach set it apart from other video generation models.
Q: What are the recommended use cases?
The model is ideal for applications requiring high-quality video generation from static images, particularly when 480P resolution is sufficient. It's well-suited for content creation, video editing, and creative applications where converting still images to dynamic videos is desired.
