InternVL2-40B
Property | Value |
---|---|
Parameter Count | 40.1B parameters |
Model Type | Image-Text-to-Text Multimodal |
License | MIT |
Papers | InternVL Paper, GPT-4V Comparison Paper |
What is InternVL2-40B?
InternVL2-40B is a state-of-the-art multimodal large language model that combines InternViT-6B-448px-V1-5 for vision processing and Nous-Hermes-2-Yi-34B for language understanding. It represents a significant advancement in multimodal AI, trained with an 8k context window and capable of handling complex visual-linguistic tasks.
Implementation Details
The model architecture integrates sophisticated vision and language components through an MLP projector, enabling seamless processing of images and text. It supports multiple deployment options, including 16-bit precision and 8-bit quantization, making it adaptable to various computational resources.
- Context window of 8k tokens
- Support for multiple images and video processing
- Comprehensive document and chart comprehension capabilities
- Advanced OCR and scene text understanding
Core Capabilities
- Achieves 93.9% accuracy on DocVQA test set
- Demonstrates 86.2% accuracy on ChartQA tasks
- Excels in cultural understanding with 80.6% on CCBench
- Superior performance in video understanding with 72.5% on MVBench
- Strong visual grounding capabilities with 90.3% average accuracy
Frequently Asked Questions
Q: What makes this model unique?
InternVL2-40B stands out for its exceptional performance across various multimodal tasks, often surpassing commercial models. Its ability to handle multiple images, video content, and complex document understanding makes it particularly versatile for real-world applications.
Q: What are the recommended use cases?
The model excels in document analysis, chart interpretation, OCR tasks, scientific problem-solving, and cultural understanding. It's particularly well-suited for applications requiring sophisticated visual-linguistic reasoning, such as automated document processing, content analysis, and intelligent visual assistance.