---
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`](https://github.com/NVIDIA/structured-data-models) for inference:

```bash
pip install git+https://github.com/NVIDIA/structured-data-models.git
```

Load the pretrained model and predict class probabilities:

```python
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](https://github.com/NVIDIA/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`.