Florence 2 (without flash attn): Advancing a Unified Representation for a Variety of Vision Tasks ⚠️ This is a modified version of Florence 2 that modifies the custom modeling florence2.py file to remove the need for installing flash attn package (by hijacking the flash attn methods and replacing with regular attention). It probably has impact in performance. 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 size Model Desc…
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