DC-research/TEMPO
The official code for "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)". TEMPO is one of the very first open source Time Series Foundation Models for forecasting task v1.0 version.
This project helps operations managers, financial analysts, and supply chain professionals predict future trends from their time-series data. You input historical data, such as sales figures, stock prices, or energy consumption, and it provides accurate forecasts for what's likely to happen next. This is useful for anyone needing to make decisions based on future predictions without extensive model training.
133 stars. No commits in the last 6 months.
Use this if you need to quickly generate forecasts for various time-series datasets without the need to train a new model from scratch for each unique dataset.
Not ideal if you require probabilistic forecasts or need to integrate diverse data types beyond time-series, such as images or specialized text data, in a single forecasting model.
Stars
133
Forks
20
Language
Python
License
MIT
Category
Last pushed
Feb 23, 2025
Commits (30d)
0
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