InternVL2-2B
| Property | Value |
|---|---|
| Parameter Count | 2.21B |
| License | MIT |
| Paper | InternVL Paper |
| Architecture | InternViT-300M-448px + InternLM2-chat-1_8b |
What is InternVL2-2B?
InternVL2-2B is a powerful multimodal large language model that combines vision and language capabilities. It's part of the InternVL 2.0 series and represents a significant advancement in multimodal AI, featuring an 8k context window and specialized architecture for handling multiple images, long texts, and videos.
Implementation Details
The model architecture consists of three main components: InternViT-300M-448px for vision processing, an MLP projector for feature alignment, and InternLM2-chat-1_8b for language understanding. It supports BF16 precision and can be deployed with various quantization options including 8-bit and 4-bit configurations.
- Trained with 8k context window
- Supports multiple GPU deployment
- Compatible with transformers library version 4.37.2
- Offers streaming output capabilities
Core Capabilities
- Document and chart comprehension (86.9% on DocVQA)
- Scene text understanding and OCR tasks
- Video analysis (60.2% on MVBench)
- Multi-image processing and understanding
- Cultural understanding and integrated multimodal reasoning
- Real-time visual grounding (77.7% average on RefCOCO benchmarks)
Frequently Asked Questions
Q: What makes this model unique?
InternVL2-2B stands out for its balanced performance across various multimodal tasks while maintaining a relatively compact size. It demonstrates competitive capabilities comparable to proprietary commercial models in areas like document understanding, OCR, and video analysis.
Q: What are the recommended use cases?
The model excels in document analysis, chart interpretation, video understanding, and general visual-linguistic tasks. It's particularly suitable for applications requiring comprehensive understanding of both visual and textual content, such as document processing systems, multimedia analysis tools, and interactive AI assistants.
