Video-LLaVA-7B-hf
| Property | Value |
|---|---|
| Parameter Count | 7.37B |
| Model Type | Multimodal LLM |
| Base Model | Vicuna-13b-v1.5 |
| License | Apache 2.0 (Research Preview) |
| Paper | View Paper |
What is Video-LLaVA-7B-hf?
Video-LLaVA is an advanced multimodal model that bridges the gap between video and image understanding. Built by the LanguageBind team, it represents a significant advancement in unified visual processing, capable of handling both images and videos through a unique alignment-before-projection approach.
Implementation Details
The model leverages a sophisticated architecture that combines transformer-based language modeling with unified visual representation processing. It's implemented using the Hugging Face Transformers library and uses BF16 tensor types for optimal performance.
- Built on the Vicuna-13b-v1.5 foundation model
- Trained on diverse datasets including LLaVA for images and Video-ChatGPT for videos
- Implements unified visual representations through pre-projection alignment
Core Capabilities
- Processes both images and videos in a unified framework
- Generates interleaved responses for mixed image-video inputs
- Handles complex visual understanding tasks
- Supports multimodal instruction following
Frequently Asked Questions
Q: What makes this model unique?
Video-LLaVA's distinctive feature is its ability to process both images and videos through a unified approach, despite not being trained on image-video pairs. This is achieved through its innovative alignment-before-projection methodology.
Q: What are the recommended use cases?
The model is ideal for applications requiring multimodal understanding, such as video analysis, image description, visual question answering, and tasks requiring interpretation of mixed visual media. It's particularly suited for research and non-commercial applications due to its licensing terms.
