Fine tuning Florence 2 with DOCVQA dataset. Quick!
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model card: huggingface.co/microsoft/Flor...
Notebook: colab.research.google.com/dri...
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What is Florence 2?
Microsoft's latest innovation in vision AI. This advanced vision foundation model seamlessly integrates computer vision and vision-language tasks through a unified, prompt-based representation. Florence-2 excels in tasks like image captioning, object detection, grounding, and segmentation, utilizing the extensive FLD-5B dataset. This dataset comprises over 5.4 billion annotations across 126 million images, ensuring comprehensive and high-quality visual data.
Florence-2's architecture features a sequence-to-sequence structure, combining a DaViT vision encoder with a transformer-based multi-modal encoder-decoder, enabling it to generate accurate and detailed results from text prompts. The model is designed to handle complex spatial hierarchies and semantic granularities, making it a versatile and powerful tool for various applications.
Integrated into Azure's Cognitive Service for Vision, Florence-2 is accessible for developers to create cutting-edge, market-ready vision applications. Its robust zero-shot and fine-tuning capabilities make it a standout in the field, offering unprecedented performance and efficiency. Florence-2 represents a significant advancement in AI, setting a new standard for vision foundation models.