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timesfm-forecasting

Performs zero-shot time-series forecasting with Google's TimesFM: CSV preparation, quantile forecasts, covariates and held-out evaluation. Downloads a checkpoint from Hugging Face.

View on GitHub
Kind
Skill
Works with
Claude Code, Codex, Cursor, Gemini / Antigravity
Source
Scientific Agent Skills (K-Dense) @ 5f2bc0341354
Path
skills/timesfm-forecasting/SKILL.md
Jobs
Implementation
Topics
Machine learning

Credit

Made by
K-Dense-AI
Original
github.com/K-Dense-AI/scientific-agent-skills/blob/5f2bc03413…
License
MIT

Listed by Skill Manifest; not made by us.

InstallInstall it by hand, following the source.
gh skill install K-Dense-AI/scientific-agent-skills timesfm-forecasting
Install factsScanned 2 Nov 2026
Adds
  • .claude/skills/timesfm-forecasting/ (the skill folder)
  • 8 file(s) the skill refers to
Runs scripts
Yes
  • scripts/check_system.py
  • scripts/forecast_csv.py
  • allowed-tools includes Bash
  • shell block in the text
Uses the network
Yes
  • downloads Python packages
Needs secrets
None found
Source revision
5f2bc0341354
Licence
MIT
Last activity
26 Oct 2026
Review
Reviewed

Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.

  • Only the main file is read; other files in the folder are not scanned
# 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](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](https://github.com/google-research/timesfm#license-notice-for-pretrained-weights).

Use TimesFM for forecasting an ordered temporal target without task-specific
…