v0.0.33

Features

• TabPFN-3 foundation model: Added support for TabPFN-3 via foundationforecast>=0.1.6. Use the existing TabPFN class with model_path; TabPFN-2 remains the default.

  import pandas as pd
  from tabpfn_time_series import TabPFNMode
  from timecopilot.models.foundation.tabpfn import TABPFN_V2_MODEL, TABPFN_V3_MODEL, TabPFN
  
  df = pd.read_csv(
      "https://timecopilot.s3.amazonaws.com/public/data/air_passengers.csv",
      parse_dates=["ds"],
  )
  
  model = TabPFN(
      model_path=TABPFN_V3_MODEL,
      mode=TabPFNMode.LOCAL,
      context_length=32768,
      alias="TabPFN-3",
  )
  assert model.model_path == TABPFN_V3_MODEL

  License note: TabPFN-2.6+ and TabPFN-3 weights use the TabPFN Non-Commercial license. First LOCAL use requires accepting terms at ux.priorlabs.ai (TABPFN_TOKEN). TabPFN-3 is LOCAL-only today.

• TabPFN family notebook: Added tabpfn-family example notebook comparing TabPFN-2 and TabPFN-3 with prediction intervals.

Dependencies

• Bumped foundationforecast from >=0.1.3 to >=0.1.6 (TabPFN-3 via model_path, tabpfn-time-series>=1.2.0).

CI

• Added TABPFN_TOKEN secret and TabPFN checkpoint cache for LOCAL integration tests.

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Full Changelog: v0.0.32...v0.0.33