InternVL2_5-78B-MPO
| Property | Value |
|---|---|
| Vision Model | InternViT-6B-448px-V2_5 |
| Language Model | Qwen2.5-72B-Instruct |
| License | MIT License (with Qwen License components) |
| Paper | arXiv:2411.10442 |
What is InternVL2_5-78B-MPO?
InternVL2_5-78B-MPO is a state-of-the-art multimodal large language model that combines advanced vision processing with powerful language understanding. It's built on a "ViT-MLP-LLM" architecture, integrating InternViT for vision processing with Qwen2.5-72B-Instruct for language tasks, connected through an MLP projector.
Implementation Details
The model utilizes a sophisticated architecture that processes images through dynamic resolution strategy with 448×448 pixel tiles. It implements Mixed Preference Optimization (MPO), combining preference loss, quality loss, and generation loss to enhance model performance.
- Employs pixel unshuffle operation to reduce visual tokens to one-quarter
- Supports multi-image and video data processing
- Uses DPO for preference loss and BCO for quality loss
- Implements advanced batch processing capabilities
Core Capabilities
- Multi-modal reasoning and dialogue
- Dynamic image resolution handling
- Video understanding and description
- Multi-image comparative analysis
- Streaming output generation
Frequently Asked Questions
Q: What makes this model unique?
The model's uniqueness lies in its Mixed Preference Optimization approach, which combines three types of loss functions to enhance reasoning abilities and response quality. It also features a sophisticated multi-modal architecture capable of handling both images and videos with dynamic resolution processing.
Q: What are the recommended use cases?
The model excels in various scenarios including image description, multi-image comparison, video analysis, and complex visual reasoning tasks. It's particularly well-suited for applications requiring detailed visual understanding and natural language interaction.
