Hugging Face has released Docmatix, a comprehensive dataset designed to enhance vision-language models (VLMs) for document understanding. Docmatix includes 9,500,000 question/answer pairs across 2,444,750 images, aiming to bridge the gap between open-source and proprietary VLMs like GPT-4. This dataset addresses the limitations of open-source models in document visual question answering, providing extensive data coverage to improve practical applications. Additionally, advancements in document retrieval have been made with the introduction of ColPali, a new model that leverages Vision Language Models to extract high-quality embeddings from document images, outperforming current systems.