OmniFusion
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Paper | ArXiv Link |
| Base Model | Mistral-7B |
| Visual Encoders | CLIP-ViT-L, Dino V2 |
What is OmniFusion?
OmniFusion is an advanced multimodal AI model that extends traditional language processing capabilities by integrating multiple data modalities. Built on Mistral-7B, it particularly excels at processing images through its innovative dual-encoder architecture. The latest version (1.1) notably includes Russian language support and achieves state-of-the-art performance on various visual-language tasks.
Implementation Details
The model employs a sophisticated architecture combining CLIP-ViT-L and Dino V2 visual encoders with a custom adapter mechanism. This adapter efficiently maps visual information to the language model's textual space, enabling seamless multimodal understanding.
- Two-stage training process: adapter pre-training and full model fine-tuning
- Custom tokens for visual data marking in text sequences
- Comprehensive training dataset including caption, VQA, and conversation tasks
Core Capabilities
- Superior performance on TextVQA (48.93%) and ScienceQA (68.02%)
- Bilingual support (English and Russian)
- Advanced visual dialogue capabilities with high NDCG scores
- Efficient processing of complex visual-textual queries
Frequently Asked Questions
Q: What makes this model unique?
OmniFusion's distinctive feature is its dual-encoder architecture and specialized adapter mechanism, allowing for superior multimodal understanding while maintaining computational efficiency. The ability to process both English and Russian makes it particularly versatile.
Q: What are the recommended use cases?
The model excels in image-text interaction tasks, including visual question answering, image captioning, and multimodal dialogue. It's particularly suited for applications requiring detailed visual understanding and natural language interaction in both English and Russian.
