SmolDocling
256M VLM for end-to-end document AI
SmolDocling launched on March 25, 2025 with 158 votes, #269 of 7,215 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
SmolDocling, from Hugging Face and IBM Research, is the ultra-compact (256M) open VLM for end-to-end document conversion. Extracts text, layout, tables, code, and more from images.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
SmolDocling is a multimodal Image-Text-to-Text model designed for efficient document conversion. It retains Docling's most popular features while ensuring full compatibility with Docling through seamless support for DoclingDocuments . This model was presented in the paper SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion . You can use transformers , vllm , or onnx to perform inference, and Docling to convert results to variety of output formats (md, html, etc.): # Prerequisites: # pip install torch # pip install docling_core # pip install transformers import torch from docling_core.types.doc import DoclingDocument from…from huggingface.co
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