VideoLLaMA2-7B
| Property | Value |
|---|---|
| Parameter Count | 8.03B parameters |
| License | Apache 2.0 |
| Architecture | CLIP ViT-Large + Mistral-7B |
| Paper | arxiv:2406.07476 |
| Training Frames | 8 frames |
What is VideoLLaMA2-7B?
VideoLLaMA2-7B is a state-of-the-art multimodal large language model designed for sophisticated video and image understanding. It combines a CLIP-based visual encoder (ViT-Large-Patch14-336) with a Mistral-7B-Instruct-v0.2 language decoder to process and analyze visual content while generating natural language responses.
Implementation Details
The model architecture integrates spatial-temporal modeling capabilities with advanced audio understanding. It processes sequences of 8 frames and utilizes BF16 tensor precision for efficient computation. The implementation is built on the Transformers library and supports both video and image processing tasks.
- Visual processing through CLIP ViT-Large architecture
- Language understanding via Mistral-7B decoder
- Support for both video and image modalities
- Efficient BF16 precision computation
Core Capabilities
- Video Question Answering and Captioning
- Multi-Choice Video Analysis
- Open-Ended Video Understanding
- Image Analysis and Description
- Temporal Relationship Processing
Frequently Asked Questions
Q: What makes this model unique?
VideoLLaMA2-7B stands out for its ability to process both videos and images with advanced spatial-temporal modeling. It's built on state-of-the-art architectures and can handle complex visual understanding tasks while maintaining natural language interaction capabilities.
Q: What are the recommended use cases?
The model excels in video content analysis, including detailed scene description, object interaction analysis, and temporal event understanding. It's particularly suitable for applications requiring sophisticated video understanding, content description, and question-answering about visual content.
