RolmOCR utilizes a complete offline running architecture, which provides significant security advantages over cloud services:
- No need to send out sensitive document data to avoid the risk of privacy leakage.
- The operation process does not rely on external network connection, higher stability
- Supports private deployment of on-premises servers
The technical implementation is based on the vLLM local reasoning framework and the deployment process consists of three key steps:
- Download pre-trained model from Hugging Face (~15GB storage)
- Configuring the Python 3.8+ runtime environment and vLLM dependencies
- Start the local REST API service (default port 8000)
The program has been evaluated for security by several financial institutions and is particularly suitable for processing:
- Contract documents containing customer information
- Medical records of medical institutions
- Confidential technical information of R&D institutions
Deployed to achieve a steady processing rate of 3-5 pages per second.
This answer comes from the articleRolmOCR: Document OCR Model for Recognizing Handwritten and Slanted CharactersThe
May not be reproduced without permission:AI productivity tools " RolmOCR's Local Deployment Model Ensures Data Privacy and Security
English 
简体中文 
日本語 
Deutsch 
Português do Brasil