sap-ai-research/contexttab · Update pipeline tag and add library name

2 days ago

This PR updates the model card for ConTextTab to accurately reflect its capabilities and improve discoverability on the Hugging Face Hub.

Pipeline Tag: Changed pipeline_tag from tabular-classification to other because the model supports both tabular classification and regression tasks, as indicated in the "Basic Usage" section.
Library Name: Added library_name: contexttab to the metadata, as the model provides its own Python library for usage, evident from the import statements in the sample code.

No changes were made to the paper link, as an arXiv link is already present.

Update pipeline tag and add library name7720de4e

marekpolewczyk changed pull request status to merged 2 days ago

MaximilianSchambach

SAP AI Research org 2 days ago

Thanks for updating!

Nishgop

1 day ago

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edited 1 day ago

@MaximilianSchambach , @nielsr : Just wanted to give you a heads-up on running your Kaggle and Colab notebooks.

I'm encountering issues with package installations and imports, which are preventing the notebook from running correctly.

1. Dependency Conflicts (from pip):
First, pip is reporting numerous dependency resolution errors. Key conflicts include:

torch ecosystem: My installed torch 2.7.1 is incompatible with torchaudio, torchvision, and fastai, all of which expect torch 2.6.0 (or an earlier version).
pyarrow: My pyarrow 20.0.0 is too new for cudf/pylibcudf (which need an older version).
scikit-learn: My scikit-learn 1.7.0 is too new for category-encoders and sklearn-compat.
google-colab related packages: There are conflicts with google-colab's expected versions of pandas, google-auth, requests, tornado, and notebook.
numpy: My numpy 1.26.4 is incompatible with cesium (which expects numpy 2.x).

2. torchvision Circular Import Error:
Following the installation attempts, I'm also getting an AttributeError: partially initialized module 'torchvision' has no attribute 'extension' (most likely due to a circular import).

Let me know your thoughts on how best to proceed!

Colab:
AttributeError: partially initialized module 'torchvision' has no attribute 'extension' (most likely due to a circular import)
/usr/local/lib/python3.11/dist-packages/torchvision/_meta_registrations.py in wrapper(fn)
16 def register_meta(op_name, overload_name="default"):
17 def wrapper(fn):
---> 18 if torchvision.extension._has_ops():
19 get_meta_lib().impl(getattr(getattr(torch.ops.torchvision, op_name), overload_name), fn)
20 return fn

Kaggle:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
bigframes 2.8.0 requires google-cloud-bigquery-storage<3.0.0,>=2.30.0, which is not installed.
pylibcudf-cu12 25.2.2 requires pyarrow<20.0.0a0,>=14.0.0; platform_machine == "x86_64", but you have pyarrow 20.0.0 which is incompatible.
cudf-cu12 25.2.2 requires pyarrow<20.0.0a0,>=14.0.0; platform_machine == "x86_64", but you have pyarrow 20.0.0 which is incompatible.
datasets 3.6.0 requires fsspec[http]<=2025.3.0,>=2023.1.0, but you have fsspec 2025.5.1 which is incompatible.
category-encoders 2.7.0 requires scikit-learn<1.6.0,>=1.0.0, but you have scikit-learn 1.7.0 which is incompatible.
cesium 0.12.4 requires numpy<3.0,>=2.0, but you have numpy 1.26.4 which is incompatible.
google-colab 1.0.0 requires google-auth==2.38.0, but you have google-auth 2.40.3 which is incompatible.
google-colab 1.0.0 requires notebook==6.5.7, but you have notebook 6.5.4 which is incompatible.
google-colab 1.0.0 requires pandas==2.2.2, but you have pandas 2.2.3 which is incompatible.
google-colab 1.0.0 requires requests==2.32.3, but you have requests 2.32.4 which is incompatible.
google-colab 1.0.0 requires tornado==6.4.2, but you have tornado 6.5.1 which is incompatible.
sklearn-compat 0.1.3 requires scikit-learn<1.7,>=1.2, but you have scikit-learn 1.7.0 which is incompatible.
pandas-gbq 0.29.1 requires google-api-core<3.0.0,>=2.10.2, but you have google-api-core 1.34.1 which is incompatible.
torchaudio 2.6.0+cu124 requires torch==2.6.0, but you have torch 2.7.1 which is incompatible.
torchvision 0.21.0+cu124 requires torch==2.6.0, but you have torch 2.7.1 which is incompatible.
fastai 2.7.19 requires torch<2.7,>=1.10, but you have torch 2.7.1 which is incompatible.
bigframes 2.8.0 requires google-cloud-bigquery[bqstorage,pandas]>=3.31.0, but you have google-cloud-bigquery 3.25.0 which is incompatible.
bigframes 2.8.0 requires rich<14,>=12.4.4, but you have rich 14.0.0 which is incompatible.
jupyter-kernel-gateway 2.5.2 requires jupyter-client<8.0,>=5.2.0, but you have jupyter-client 8.6.3 which is incompatible.