How VLMs Work and Key Models

A guide summarizing the core concepts and ecosystem of Vision Language Models (VLMs), which are trained on images and text simultaneously to perform various tasks such as visual question answering (VQA), image captioning, and document understanding.

Key Features and Functions

• Multimodal Learning: Generative models that produce text output from image and text inputs.
• Versatility: Excellent zero-shot capabilities, able to process various visual materials such as documents and web pages.
• Spatial Understanding: Capable of outputting bounding boxes for object detection or generating segmentation masks.

Open-Source Models and Evaluation Tools

• Key Models: Various models with different parameter sizes and licenses, such as LLaVA 1.6, DeepSeek-VL, CogVLM, and Qwen-VL, are available through the Hugging Face Hub.
• Model Selection: You can select a model suited to your use case by utilizing Vision Arena, which is based on human preferences, and the Open VLM Leaderboard, which provides various benchmark metrics.