Install & Compatibility
Where this runs
tested against v2.1.1 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
py 3.10
✕ build_error
✓ 87.5s
py 3.11
✕ build_error
✓ 81.7s
py 3.12
✕ build_error
✓ 72.8s
py 3.13
✕ build_error
✓ 69s
py 3.9
✕ build_error
✕ timeout
5094MB installed
● package 5094MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
TabICLClassifier
✓ from tabicl import TabICLClassifier
✗ from tabicl import TabICL
TabICLRegressor
✓ from tabicl import TabICLRegressor
✗ from tabicl import TabICL
InferenceConfig
✓ from tabicl import InferenceConfig
✗ from tabicl import TabICL
Basic usage of TabICL for tabular data prediction.
import pandas as pd
from tabicl import TabICL
# Load or create a pandas DataFrame with your data
# data = pd.read_csv('your_data.csv')
# Initialize the model
model = TabICL(pretrained=True)
# Example: predict on a dataset (adjust as per your task)
# predictions = model.predict(data)
print('TabICL model loaded successfully')
Upgrade
Version history
2.1.1latest on PyPI · released Apr 29, 2026
Audit
Dependencies
torchrequiredTabICL requires PyTorch for model inference and training.
pandasrequiredUsed for data loading and preprocessing.