Spectro 2 B

Introduction

Spectro-2B is an advanced video generation model developed by SVECTOR, featuring 2 billion parameters. It is designed to produce high-quality, transformer-based video outputs at 24 FPS, utilizing cutting-edge transformer techniques and 3D modeling to generate, process, and understand video data.

Architecture

Transformer3DModel: The core of Spectro-2B, this module processes video data across spatial and temporal dimensions using multi-head attention, ensuring contextual coherence with 28 layers and a positional embedding system (rope).

CausalVideoAutoencoder: This component manages latent space compression and decompression, maintaining computational efficiency and high fidelity in output through techniques like residual connections and latent representation.

Training

The model's architecture supports efficient handling of video data through a structured approach: data preprocessing, transformer processing, latent space compression, and video generation. Key innovations include positional embeddings, attention mechanisms, and an efficient latent representation, optimizing computational resources for high-quality video production.

Guide: Running Locally

1. Clone the repository:

   git clone https://huggingface.co/SVECTOR-CORPORATION/Spectro-2B.git
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the model:

   python generate_video.py --input "input_data.mp4" --output "output_video.mp4"
   

For optimal performance, consider using cloud-based GPUs such as those offered by AWS, Google Cloud, or Azure.

License

Spectro-2B is released under the Creative Commons BY-NC 4.0 license, permitting non-commercial use with attribution.