Florence 2: Advancing a Unified Representation for a Variety of Vision Tasks Model Summary This Hub repository contains a HuggingFace's transformers implementation of Florence 2 model from Microsoft. Florence 2 is an advanced vision foundation model that uses a prompt based approach to handle a wide range of vision and vision language tasks. Florence 2 can interpret simple text prompts to perform tasks like captioning, object detection, and segmentation. It leverages our FLD 5B dataset, containing 5.4 billion annotations across 126 million images, to master multi task learning. The model's sequence to sequence architecture enables it to excel in both zero shot and fine tuned settings, proving to be a competitive vision foundation model. Resources and Technical Documentation: + Florence 2 technical report. + Jupyter Notebook for inference and visualization of Florence 2 large model Model Model size Model Description Florence 2 base[[HF]](https://huggingface.co/microsoft/Florence 2 base) 0.23B Pretrained model with FLD 5B Florence 2 large[[HF]](https://huggingface.co/microsoft/Florence 2 large) 0.77B Pretrained model with FLD 5B Florence 2 base ft[[HF]](https://huggingface.co/microso…
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