DeepSeek-VL2: Mixture-of-Experts Vision-Language Models
DeepSeek-VL2 is an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models that significantly improves upon its predecessor, DeepSeek-VL. This model series demonstrates superior capabilities across various tasks, including:
- Visual Question Answering: Answer questions based on visual content.
- Optical Character Recognition: Recognize and process text from images.
- Document/Table/Chart Understanding: Analyze and interpret structured data.
- Visual Grounding: Relate visual content to textual descriptions.
Key Features:
- Variants: Includes DeepSeek-VL2-Tiny, DeepSeek-VL2-Small, and DeepSeek-VL2 with 1.0B, 2.8B, and 4.5B activated parameters respectively.
- Performance: Achieves competitive or state-of-the-art performance with similar or fewer activated parameters compared to existing models.
- Installation: Easy installation with Python and dependencies.
- Inference Examples: Provides simple inference examples for single and multiple images, as well as incremental prefilling.
- Gradio Demo: A demo implementation for interactive use.
Benefits:
- Advanced Multimodal Understanding: Enhances the ability to process and understand complex visual and textual data.
- Open Source: Available for both academic and commercial use under the MIT License.
- Community Support: Active contributions and feedback mechanisms for continuous improvement.
