Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab VeloxTrend Ultrarix Capital Partners Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-FranΓ§ois Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Publication

Building Local OCR Application SmolDocling: A Step-by-Step Guide [Part 2]
Latest   Machine Learning

Building Local OCR Application SmolDocling: A Step-by-Step Guide [Part 2]

Last Updated on April 15, 2025 by Editorial Team

Author(s): Youssef Hosni

Originally published on Towards AI.

Building Local OCR Application SmolDocling: A Step-by-Step Guide [Part 2]

If you want to build a Local OCR application so that you do not need to send your documents to APIs. You can use 𝐒𝐦𝐨π₯πƒπ¨πœπ₯𝐒𝐧𝐠, which is an ultra-compact vision-language model for end-to-end multi-modal document conversion that can be used for LocalOCR.

𝗦𝗺𝗼𝗹𝗗𝗼𝗰𝗹𝗢𝗻𝗴 is a compact 256M open-source vision language model designed for OCR. It offers end-to-end document conversion without complex pipelines, allowing a single small model to handle everything.

It’s fast and efficient, processing a page in just 0.35 seconds on a consumer GPU with less than 500MB VRAM. Despite its small size, it delivers high accuracy, outperforming models 27Γ— larger in full-page transcription, layout detection, and code recognition.

In this two-part hands-on tutorial, we’ll build a local OCR application using 𝗦𝗺𝗼𝗹𝗗𝗼𝗰𝗹𝗢𝗻𝗴. In the second part, we’ll develop the OCR web application, and we’ll integrate everything from the first part and create the application interface using streamlit.

Set up the Working EnvironmentBuild the OCR Pipeline with SmolDoclingBuild the Streamlit ApplicationRun the OCR Application

You can find the codes and data used in this article in this GitHub Repo.

Most insights I share in Medium have previously been shared in my weekly newsletter, To Data & Beyond.

If you want to be up-to-date with the frenetic world… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.

Published via Towards AI

Feedback ↓