PriorLabs/TabPFN v6.4.0

on GitHub

Added

• Introduces dedicated method for fitting with differentiable input called fit_with_differentiable_input() (#752)
• Pass through kwargs in FinetunedTabPFNClassifier and FinetunedTabPFNRegressor predict and predict_proba methods to allow additional options like output_type='full' (#772)
• Add MPS memory limiting to prevent macOS system crashes when using Apple Silicon GPUs. Memory is automatically limited to 70% of recommended max on import. Configurable via TABPFN_MPS_MEMORY_FRACTION environment variable. (#773)
• Added TabPFNCUDAOutOfMemoryError and TabPFNMPSOutOfMemoryError for GPU out-of-memory errors during prediction with large test sets, providing helpful guidance on batching predictions. (#774)

Changed

• Remove upper version limits on dependencies (#764)

• Refactored preprocessing pipeline:

  • Introduced FeatureSchema system to track column metadata through transformations, replacing raw categorical index lists.
  • Added PreprocessingPipeline and PreprocessingStep interfaces for modular transformations and updated all preprocessing steps.
  • Added TabPFNLabelEncoder for centralized label validation and metadata extraction.

  (#767)

• • Introduces AddSVDFeaturesStep as a dedicated preprocessing step for SVD feature generation
  • Removes SVD-related functionality from ReshapeFeatureDistributionsStep
  • Extracts utility functions to a new tabpfn/preprocessing/steps/utils.py module

  (#768)

• SVD preprocessing is now applied after categorical encoding for more robustness. Note that this may result in slight variations in final outcomes compared to previous versions. (#779)

• Remove random_state parameter from AddFingerprintFeaturesStep; fingerprint hashing is now fully deterministic and no longer uses a random salt. Predictions will differ slightly from previous versions due to the changed fingerprint values. (#780)

• Fix bug related to column ordering in ordinal encoder by introducing OrderPreservingColumnTransformer. Note that this change can cause slight differences in final outcomes compared to previous versions. (#788)

Fixed

• Fix race condition when model is downloaded simultaneously by multiple processes (#738)
• Fix infinite loop in fingerprint hashing when rows contain inf or very large floats (#780)

Deprecated

• Removes "scaler" as an option for global_transformer_name in PreprocessorConfig (#768)