nixtla
by Nixtla (organization)
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… (description from the project’s GitHub page)
Repository facts
- Stars
- 4,026
- Forks
- 341
- Open issues and pull requests
- 63
- Primary language
- Jupyter Notebook
- License
- Other license
- Owner
- Nixtla · Organization
- Created
- Sep 23, 2021
- Last push
- Oct 15, 2026
Topics
Related projects
Projects that share this one’s GitHub topics.
Rank 8,301: TimeCopilot/timecopilot
TimeCopilot: the GenAI Forecasting Agent. Built on LLMs and Time Series Foundation Models, it lets you forecast, cross-validate, and detect anomalies using multiple foundation mod…
624 starsPythonMITLast push Oct 15, 2026
Rank 1,323: amazon-science/chronos-forecasting
Chronos: Pretrained Models for Time Series Forecasting
6,135 starsPythonApache-2.0Last push Oct 5, 2026
Rank 3,266: AIStream-Peelout/flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
2,305 starsPythonGPL-3.0Last push Oct 12, 2026
Rank 817: yzhao062/pyod
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic work…
10,046 starsPythonBSD-2-ClauseLast push Oct 12, 2026
Rank 6,748: moment-timeseries-foundation-model/moment
MOMENT: A Family of Open Time-series Foundation Models, ICML'24
858 starsTypeScriptMITLast push Feb 10, 2026
Rank 4,384: time-series-foundation-models/lag-llama
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
1,600 starsPythonApache-2.0Last push Jun 6, 2025