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transformers 5 support (CVE-2026-1839): Widened the transformers upper bound to <6 and huggingface-hub to <2.0 so TimeCopilot can install transformers>=5.0.0rc3, which remediates CVE-2026-1839. Reaching transformers 5 also required bumping tfc-t0 to >=0.2.0, timecopilot-granite-tsfm to >=0.2.1, timecopilot-toto to >=0.1.7, and timecopilot-timesfm to >=0.3.0 (previously pinned huggingface-hub<1 / transformers<5, or broken under huggingface-hub>=1). See #359 and #360.
Clean model cache option: Forecaster now accepts a clean_cache flag. When enabled, it runs Python garbage collection and clears the CUDA cache after each model runs, reducing peak memory when chaining many foundation models. See #358.
Python version guards for granite-backed models: FlowState and PatchTSTFM now raise a clear ImportError on unsupported Python versions (they require >=3.11,<3.14, matching timecopilot-granite-tsfm), consistent with the existing TiRex and T0 guards. The timecopilot-granite-tsfm dependency is gated with the same Python markers so resolution succeeds on Python 3.10/3.14.
Toto compatibility with huggingface-hub 1.x: Toto failed to load under huggingface-hub>=1 (Toto._from_pretrained() missing 2 required keyword-only arguments: 'proxies' and 'resume_download'). Fixed in timecopilot-toto>=0.1.7, which no longer requires those arguments. Toto (1.0) and Toto-2 now load correctly under transformers 5.
TimesFM 2.5 compatibility with huggingface-hub 1.x: TimesFM (2.5) failed to load under huggingface-hub>=1 (TimesFM_2p5_200M_torch._from_pretrained() missing 2 required keyword-only arguments: 'proxies' and 'resume_download'). Fixed in timecopilot-timesfm>=0.3.0, which re-syncs the TimesFM 2.5 source with upstream (dropping those arguments and migrating to PyTorchModelHubMixin). TimesFM now loads correctly under transformers 5.
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transformers 5 support (CVE-2026-1839): Widened the
transformersupper bound to<6andhuggingface-hubto<2.0so TimeCopilot can installtransformers>=5.0.0rc3, which remediates CVE-2026-1839. Reaching transformers 5 also required bumpingtfc-t0to>=0.2.0,timecopilot-granite-tsfmto>=0.2.1,timecopilot-tototo>=0.1.7, andtimecopilot-timesfmto>=0.3.0(previously pinnedhuggingface-hub<1/transformers<5, or broken underhuggingface-hub>=1). See #359 and #360.Clean model cache option:
Forecasternow accepts aclean_cacheflag. When enabled, it runs Python garbage collection and clears the CUDA cache after each model runs, reducing peak memory when chaining many foundation models. See #358.Fixes
Python version guards for granite-backed models:
FlowStateandPatchTSTFMnow raise a clearImportErroron unsupported Python versions (they require>=3.11,<3.14, matchingtimecopilot-granite-tsfm), consistent with the existingTiRexandT0guards. Thetimecopilot-granite-tsfmdependency is gated with the same Python markers so resolution succeeds on Python 3.10/3.14.Toto compatibility with huggingface-hub 1.x:
Totofailed to load underhuggingface-hub>=1(Toto._from_pretrained() missing 2 required keyword-only arguments: 'proxies' and 'resume_download'). Fixed intimecopilot-toto>=0.1.7, which no longer requires those arguments.Toto(1.0) andToto-2now load correctly under transformers 5.TimesFM 2.5 compatibility with huggingface-hub 1.x:
TimesFM(2.5) failed to load underhuggingface-hub>=1(TimesFM_2p5_200M_torch._from_pretrained() missing 2 required keyword-only arguments: 'proxies' and 'resume_download'). Fixed intimecopilot-timesfm>=0.3.0, which re-syncs the TimesFM 2.5 source with upstream (dropping those arguments and migrating toPyTorchModelHubMixin).TimesFMnow loads correctly under transformers 5.Full Changelog: v0.0.28...v0.0.29
This discussion was created from the release v0.0.29.
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