AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

arXiv:2404.16233v1 Announce Type: new
Abstract: AutoGluon-Multimodal (AutoMM) is introduced as an open-source AutoML library designed specifically for multimodal learning. Distinguished by its exceptional ease of use, AutoMM enables fine-tuning of foundational models with just three lines of code. Supporting various modalities including image, text, and tabular data, both independently and in combination, the library offers a comprehensive suite of functionalities spanning classification, regression, object detection, semantic matching, and image segmentation. Experiments across diverse datasets and tasks showcases AutoMM's superior performance …

abstract arxiv autogluon automl code combination cs.ai cs.lg data fine-tuning foundation foundational foundational models image library multimodal multimodal learning tabular tabular data text type