thuml/OpenLTM
Implementations, Pre-training Code and Datasets of Large Time-Series Models
This project provides an open environment for researchers and advanced data scientists to develop, evaluate, and fine-tune large time-series models (LTMs), also known as Time Series Foundation Models (TSFMs). You can input diverse time-series data, whether for pre-training or supervised tasks, and it outputs trained models capable of advanced forecasting or feature extraction. This is for users who want to push the boundaries of time-series analysis with state-of-the-art deep learning architectures.
526 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced practitioner looking to experiment with, build, or adapt powerful deep learning models for complex time-series forecasting and analysis tasks.
Not ideal if you need a simple, out-of-the-box tool for routine time-series forecasting without deep model development or adaptation.
Stars
526
Forks
51
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jul 21, 2025
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0
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