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- google-research/timesfm
google-research/timesfm
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
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AT A GLANCE
- LANGUAGE
- Python
- LICENSE
- Apache-2.0
- USAGE
- Commercial use, redistribution OK. Keep notices; mark changes.
- ACTIVITY
- last commit 7 days ago ()
- HOMEPAGE
- https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/
- REPOSITORY
- GitHub ↗
- CATEGORY
- DATA
A summary, not legal advice.
README EXCERPT
TimesFM TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. Paper: A decoder-only foundation model for time-series forecasting, ICML 2024. (NEW!) TimesFM 3.0 Checkpoint: google/timesfm-3.0-pytorch . Checkpoints (up to 2.5): TimesFM Hugging Face Collection. Google Research blog (New blog post for TimesFM 3.0 coming soon!). TimesFM in Google 1P Products: BigQuery ML: Enterprise level SQL queries for scalability and reliability. Google Sheets: For your daily spreadsheet. Vertex Model Garden: Dockerized endpoint for agentic calling. This open version is not an officially supported Google product. Latest Model Version: TimesFM 3.0 Archived Model Versions: - 2.5: relevant code under src/timesfm . - 1.0 and 2.0: relevant code archived in the subdirectory v1 . You can pip install timesfm==1.3.0 to install an older version of this package to load them. -------------------------------------------------------------------------------- Update — August 2026 TimesFM 3.0 is out! TimesFM 3.0 introduces native multivariate time-series forecasting , flexible covariate support (both past-only and past-and-future…
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