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Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models

This blog post by Hugging Face demonstrates how to fine-tune Microsoft's Florence-2 vision-language model on the DocVQA dataset, showing that after fine-tuning the Levenshtein similarity score improved from 0 to 57.0. The post includes code walkthroughs and links to a demo space and GitHub repository.

From the source

In this post, we show an example on fine-tuning Florence on DocVQA. The authors report that Florence 2 can perform visual question answering (VQA), but the released models don't include VQA capability. Let's see what we can do!

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