Author description: TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Popularity
Repository stars4,04055,096Highest
7-day net stars——
Fork3426,399Highest
30-day trendInsufficient historyInsufficient history
Maintenance
Last push2026-11-022024-09-18
Maintenance notesNot verifiedNot verified
Repository created2021-09-232023-03-23
License & use
LicenseLicense not declaredApache-2.0 · Permissive
Cost detailsCheck current official software, hosting, model and infrastructure pricing.Check current official software, hosting, model and infrastructure pricing.
Pricing source——
First collected2026-11-032026-11-03
MetricRepository stars, not unique users or individual-skill installsRepository stars, not unique users or individual-skill installs
LanguageJupyter NotebookJupyter Notebook
About this projectAuthor description: TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Measured at2026-11-03 09:39 UTC2026-11-03 08:27 UTC
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