LLaVA-Mini-LLaMA-3.1-8B
| Property | Value |
|---|---|
| Author | ICTNLP |
| Model Size | 8B parameters |
| Paper | arXiv:2501.03895 |
| Model Hub | Hugging Face |
What is llava-mini-llama-3.1-8b?
LLaVA-Mini is a groundbreaking multimodal model that revolutionizes image and video understanding by using just one vision token, compared to the traditional 576 tokens. This innovative approach achieves comparable performance to LLaVA-v1.5 while dramatically improving efficiency and reducing computational requirements.
Implementation Details
The model implements a highly efficient architecture that reduces FLOPs by 77% and cuts VRAM usage from 360 MB/image to just 0.6 MB/image. Response latency is improved from 100ms to 40ms, enabling processing of up to 3-hour videos on standard GPU hardware with 24GB memory.
- Single token vision representation (0.17% compression rate)
- Dynamic image compression capabilities
- Supports both image and video understanding
- Compatible with high-resolution image processing
Core Capabilities
- Efficient image understanding with minimal computational overhead
- Video processing with significantly reduced memory requirements
- Low-latency responses for real-time applications
- Maintains high-quality visual understanding despite compression
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to compress visual information into a single token while maintaining performance comparable to models using 576 tokens makes it uniquely efficient. This breakthrough enables processing of longer videos and more images with limited computational resources.
Q: What are the recommended use cases?
The model is ideal for applications requiring efficient processing of images and videos, particularly in resource-constrained environments. It's especially suitable for long-form video analysis, real-time image processing, and high-resolution image understanding tasks.
