Build a Self-Scaling OCR Pipeline with Qwen 3.5 and Kubernetes
This project offers a comprehensive guide to building a production-ready OCR pipeline. It leverages the capabilities of Qwen 3.5 for accurate text recognition and extraction tasks. The architecture
This project offers a comprehensive guide to building a production-ready OCR pipeline. It leverages
the capabilities of Qwen 3.5 for accurate text recognition and extraction tasks. The architecture
utilizes Kubernetes to ensure the system can scale automatically based on demand. Users will learn
how to containerize the application components for efficient deployment. The tutorial covers the
integration of the machine learning model with orchestration tools. It addresses common challenges
in deploying OCR systems at scale in cloud environments. The repository includes configuration files
and code examples to facilitate immediate implementation. This resource is ideal for engineers
looking to automate document processing workflows reliably.