metadata
license: openmdw-1.1
base_model:
- jingang/TabICL
tags:
- relational-foundation-model
- structured-data-models
Kumo Relational
Kumo Relational is NVIDIA's pretrained foundation model for classification and regression across related tables using in-context learning. It is based on KumoRFM-2 and combines row embeddings with relational message passing.
Getting Started
Install structured-data-models for inference:
pip install git+https://github.com/NVIDIA/structured-data-models.git
Load the pretrained model and predict class probabilities:
import sdm
model = sdm.models.KumoRelational(task="classification", device="cuda")
probs = model(
x_context=x_context,
y_context=y_context,
x_query=x_query,
related_context_tables=related_context,
related_query_tables=related_query,
num_estimators=8,
)
To learn more, visit structured-data-models.
License and Third-Party Notice
Kumo Relational weights are released under OpenMDW 1.1.
Kumo Relational finetunes pretrained TabICLv2 weights, licensed under BSD-3-Clause. The upstream attribution, copyright notice, and complete BSD 3-Clause license text are preserved in THIRD-PARTY-NOTICES.txt.