metadata
license: openmdw-1.1
tags:
- tabular-foundation-model
- structured-data-models
Kumo Tabular
Kumo Tabular is NVIDIA's pretrained tabular foundation model for classification and regression.
Getting Started
Install structured-data-models for inference:
pip install structured-data-models
Use labeled examples as context to predict class probabilities for new data:
import torch
from sklearn.datasets import load_breast_cancer
import sdm
df = load_breast_cancer(as_frame=True).frame
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
table = sdm.TableTensor.from_pandas(
df=df,
stypes=sdm.infer_stypes(df, overrides={"target": "categorical"}),
device=device,
)
model = sdm.models.KumoTabular(task="classification", device=device)
with torch.amp.autocast(
device.type,
dtype=torch.float16,
enabled=device.type == "cuda",
):
probs = model(
x_context=table[:300].drop_columns("target"),
y_context=table[:300, "target"],
x_query=table[300:].drop_columns("target"),
num_estimators=8,
)
print(probs)
To learn more, visit structured-data-models.
License
Kumo Tabular weights are released under OpenMDW 1.1.