How-To Use Docling with Ollama based Vision Models Locally
AI Summary
This video provides a detailed overview of Dockling, an advanced document processing framework developed by IBM, with a focus on its newly introduced Vision Language Model (VLM) pipeline feature. Dockling excels at converting and understanding diverse document formats such as PDFs, Word documents, HTML, and images by capturing layout, tables, formulas, code blocks, and images beyond simple text extraction.
The VLM pipeline integration represents a significant advancement allowing Dockling to process documents end-to-end with a vision language model that understands both textual and visual elements for richer and more accurate document conversion compared to traditional OCR.
The video demonstrates installing Dockling locally and testing the VLM feature using an Olama-based vision model (Jama 3, 27 billion parameters) running on a GPU-enabled Ubuntu system. The presenter walks through the code, which validates the model running locally, processes a PDF document by sending page images to the vision model, and exports results in multiple formats (Markdown, HTML, JSON).
The demo highlights Dockling’s ability to handle complex documents retaining structure and content accurately, and showcases the potential for integrating vision language models to elevate document understanding and conversion workflows. The video also mentions sponsors and provides a discount for renting GPUs.
Overall, this video is valuable for those interested in AI-powered document processing, vision language models, and IBM’s Dockling framework updates.