Accelerating Document AI

📰 Hugging Face Blog

Unlock document knowledge with open-source models and custom solutions for Document AI

intermediate Published 21 Nov 2022
Action Steps
  1. Identify the type of document and task at hand
  2. Choose the best open-source model for the task, such as image classification or document question answering
  3. Use the model to build a custom solution for free
  4. Explore use cases and resources for Document AI
Who Needs to Know This

Data scientists and developers on a team can benefit from using open-source models to build custom Document AI solutions, improving workflow accessibility and efficiency

Key Insight

💡 Open-source models can be used to build custom solutions for Document AI, unlocking inaccessible knowledge in documents

Share This
📄 Unlock document knowledge with open-source models for Document AI! #DocumentAI #OpenSource

Key Takeaways

Unlock document knowledge with open-source models and custom solutions for Document AI

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Published Time: 2022-11-21T00:00:00.150Z

# Accelerating Document AI

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# [](https://huggingface.co/blog/document-ai#accelerating-document-ai) Accelerating Document AI

Published November 21, 2022

[Update on GitHub](https://github.com/huggingface/blog/blob/main/document-ai.md)

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* [Use Cases](https://huggingface.co/blog/document-ai#use-cases "Use Cases")

* [Next Steps](https://huggingface.co/blog/document-ai#next-steps "Next Steps")

* [Resources](https://huggingface.co/blog/document-ai#resources "Resources")

Enterprises are full of documents containing knowledge that isn't accessible by digital workflows. These documents can vary from letters, invoices, forms, reports, to receipts. With the improvements in text, vision, and multimodal AI, it's now possible to unlock that information. This post shows you how your teams can use open-source models to build custom solutions for free!
Document AI includes many data science tasks from [image classification](https://huggingface.co/tasks/image-classification), [image to text](https://huggingface.co/tasks/image-to-text), [document question answering](https://huggingface.co/tasks/document-question-answering), [table question answering](https://huggingface.co/tasks/table-question-answering), and [visual question answering](https://huggingface.co/tasks/visual-question-answering). This post starts with a taxonomy of use cases within Document AI and the best open-source models for those use cases.
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