DeepSeek-VL

PaliGemma 2, the next evolution in tunable vision-language models, builds upon the performant Gemma 2 models, adding the power of vision and making it easier than ever to fine-tune for exceptional performance. With PaliGemma 2, these models can see, understand, and interact with visual input, opening up a world of new possibilities. It offers scalable performance with multiple model sizes (3B, 10B, 28B parameters) and resolutions (224px, 448px, 896px). PaliGemma 2 generates detailed, contextually relevant captions for images, going beyond simple object identification to describe actions, emotions, and the overall narrative of the scene. Our research demonstrates leading performance in chemical formula recognition, music score recognition, spatial reasoning, and chest X-ray report generation, as detailed in the technical report. Upgrading to PaliGemma 2 is a breeze for existing PaliGemma users.

Florence-2-large is an advanced vision foundation model developed by Microsoft, capable of handling a wide variety of vision and vision-language tasks, such as captioning, object detection, segmentation, and OCR. Built with a sequence-to-sequence architecture, it uses the FLD-5B dataset containing over 5 billion annotations and 126 million images to master multi-task learning. Florence-2-large excels in both zero-shot and fine-tuned settings, providing high-quality results with minimal training. The model supports tasks including detailed captioning, object detection, and dense region captioning, and can process images with text prompts to generate relevant responses. It offers great flexibility by handling diverse vision-related tasks through prompt-based approaches, making it a competitive tool in AI-powered visual tasks. The model is available on Hugging Face with pre-trained weights, enabling users to quickly get started with image processing and task execution.