PyPI release (1.0.0) is incompatible with the published Hugging Face checkpoint(for kaggle); loader fix exists on main but has not been released

The current PyPI release (tabfm==1.0.0) cannot load the official Hugging Face PyTorch checkpoint (google/tabfm-1.0.0-pytorch).

After investigating the issue, it appears that this is a release mismatch rather than an architecture or checkpoint problem. The current GitHub source already contains a rewritten loader (TabFM_HF.from_pretrained() via PyTorchModelHubMixin), but PyPI still distributes the older loader implementation.

The current PyPI package (tabfm==1.0.0) cannot load the official
google/tabfm-1.0.0-pytorch checkpoint.

The published Hugging Face repository contains

classification/
model.safetensors

while the released PyPI package expects

classification/pytorch_model.bin

and calls torch.load().

This causes

FileNotFoundError:
Weights not found at ...

I noticed the current repository already contains a rewritten loader
based on PyTorchModelHubMixin (version reports 1.0.1 in the source tree),
which correctly delegates loading through Hugging Face.

Therefore, this appears to be a packaging/release mismatch rather than
an implementation bug.

The GitHub source contains the fix, but the published package used by
Kaggle and pip users still contains the older loader.

Would it be possible to publish a new PyPI release matching the current
repository so users can load the official checkpoint without patching
the loader manually?

Compare the PyPI tabfm==1.0.0 package with the current source, especially TabFM_HF.from_pretrained() and the source version reported as 1.0.1. Check the project’s packaging and release workflow, then verify that a new PyPI release loads google/tabfm-1.0.0-pytorch from Hugging Face in the Kaggle or pip use case. Done means the published package matches the current loader and no longer expects the missing pytorch_model.bin file.

Written by the indexing model from the issue text.