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timesfm-forecasting

k-dense-ai/scie…t-skills

Performs zero-shot time-series forecasting with Google's TimesFM, including regular-grid CSV preparation, quantile forecasts, XReg covariates, and held-out evaluation. Uses the Apache-licensed TimesFM 2.5 checkpoint by default and documents the distinct TimesFM 3.0 multivariate API and weight-license requirements.

  • 1990 次安装
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安装命令

npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill timesfm-forecasting

SKILL.md

TimesFM Forecasting

Choose the model/API first

The Python package version is 3.0.2; checkpoint versions are separate.

Checkpoint Interface Quantile output Usage terms
2.5, 200M timesfm.TimesFM_2p5_200M_torch, compile, forecast mean + 9 deciles, median index 5 Apache-2.0 weights; bundled CLI default
3.0, about 330M timesfm3.TimesFM3Forecaster, predict / predict_batch 9 deciles, median index 4 Downloaded weights restricted to non-commercial, non-production use

Upstream identifies 3.0 as the latest model. This skill retains 2.5 as its default local workflow because its Apache-licensed weights have different usage terms. For 3.0 multivariate targets, past-only covariates or Apple MLX, read references/timesfm3.md before adapting code. Authorized Google Cloud services have separate terms; a Cloud entitlement does not change the license of downloaded weights. See the upstream license notice.

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