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tabpfn_2_5

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Prior Labs 161

Can someone please explain the differences between these checkpoints:

tabpfn-v2.5-classifier-v2.5_default-2.ckpt
tabpfn-v2.5-classifier-v2.5_default.ckpt
tabpfn-v2.5-classifier-v2.5_large-features-L.ckpt
tabpfn-v2.5-classifier-v2.5_large-features-XL.ckpt
tabpfn-v2.5-classifier-v2.5_large-samples.ckpt
tabpfn-v2.5-classifier-v2.5_real.ckpt
tabpfn-v2.5-classifier-v2.5_real-large-features.ckpt
tabpfn-v2.5-classifier-v2.5_real-large-samples-and-features.ckpt
tabpfn-v2.5-classifier-v2.5_variant.ckpt
tabpfn-v2.5-regressor-v2.5_default.ckpt
tabpfn-v2.5-regressor-v2.5_low-skew.ckpt
tabpfn-v2.5-regressor-v2.5_quantiles.ckpt
tabpfn-v2.5-regressor-v2.5_real.ckpt
tabpfn-v2.5-regressor-v2.5_real-variant.ckpt
tabpfn-v2.5-regressor-v2.5_small-samples.ckpt
tabpfn-v2.5-regressor-v2.5_variant.ckpt

I see this in classifier.py:

            model_path:
                The path to the TabPFN model file, i.e., the pre-trained weights.
                Can be a list of paths to load multiple models. If a list is provided,
                the models are applied across different estimators.

                - If `"auto"`, the model will be downloaded upon first use. This
                  defaults to your system cache directory, but can be overwritten
                  with the use of an environment variable `TABPFN_MODEL_CACHE_DIR`.
                - If a path or a string of a path, the model will be loaded from
                  the user-specified location if available, otherwise it will be
                  downloaded to this location.

But I wasn't able to find any guidance on when to use each checkpoint.

Is it even recommended to use checkpoints other than the default one?

Any information would be appreciated.