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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`.
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