DeepSeek-VL2

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.