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NVIDIA Releases Kumo Relational for Predictions Directly From Relational Databases

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NVIDIA introduced Kumo Relational, a pretrained model for making predictions directly from relational databases, and made it available through its structured-data-models library and as an NVIDIA NIM. NVIDIA says the model uses up to 10,000 historical examples as context without requiring task-specific training or feature engineering; optional fine-tuning is also supported. NVIDIA reports that Kumo Relational outperforms supervised approaches across 41 tasks on 15 databases and surpasses AutoGluon ensembles by 8% in mean reciprocal rank (MRR) on SAP SALT. The library’s code is released under Apache 2.0, while the model weights use the OpenMDW License Agreement, version 1.1.

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Latest development10/22 02:26 (UTC+8)
NVIDIA Introduces Kumo Relational for Database Predictions Without Task-Specific TrainingHugging Face Blog

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10/22
  1. Hugging Face BlogPicks
    NVIDIA Introduces Kumo Relational for Database Predictions Without Task-Specific Training

    NVIDIA introduced Kumo Relational, a pre-trained foundation model that predicts directly from relational databases using up to 10,000 historical examples as context, without task-specific training or feature engineering. NVIDIA reports that it outperforms supervised approaches across 41 tasks on 15 databases and surpasses AutoGluon ensembles by 8% in MRR on SAP SALT. It is available through the open-source structured-data-models library or as an NVIDIA NIM, with optional fine-tuning.

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