semvec/pypi-packages huggingface dataset:
special-attentions-pack 0.3.0
A collection of sparse attention mechanisms
License: MIT
Requires Python: >=3.7

# SparseAttnFunctions  
**Efficient Implementations of Sparse Attention Mechanisms**  

This repository contains multiple optimized implementations of sparse attention techniques, specifically tailored for **CogVideo2B**. These modifications enhance computational efficiency and memory usage, making them ideal for large-scale video generation tasks.

### Key Features:  
• **Sparse Attention Variants**: Includes several approaches to sparse attention, such as windowed attention, block-sparse attention, and more.  
• **CogVideo2B Integration**: Customized to seamlessly integrate with the CogVideo2B framework, ensuring optimal performance.  
• **Efficiency**: Designed to reduce memory footprint and accelerate computation, especially for high-resolution video generation.  

### Use Cases:  
• Large-scale video generation tasks.  
• Applications requiring efficient attention mechanisms for long sequences.  

### Installation
• pip install .

### Contributing:  
Contributions are welcome! Please follow the [Contribution Guidelines](#) for more details.