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How to use Chronos Forecasting: what you can do with it

What is Chronos Forecasting? Chronos is Amazon Science's family of pretrained time series forecasting models. Chronos-2 forecasts univariate, multivariate and covariate informed tasks zero shot, Chronos-Bolt is a patch based variant the README describes as up to 250 times faster and 20 times more memory efficient than the original Chronos models of the same size, and the original Chronos models tokenize a series and score it with a language model architecture. One pip install gives you the whole family.

How do I use it? Install it with pip install chronos-forecasting; then load the pipeline with Chronos2Pipeline.from_pretrained on amazon/chronos-2 as in the README; read your history into context_df and your future covariate values into future_df. Full steps below.

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What do you want to do?

3 use cases

Quick start with Chronos Forecasting

  1. Check you have what it needs: Python with pip and `pip install chronos-forecasting`; pandas with pyarrow for the DataFrame examples; A CUDA GPU for the README example, which sets device_map to cuda.
  2. Open amazon-science/chronos-forecasting on GitHub and read the README and license.
  3. Install it with pip install chronos-forecasting
  4. Load the pipeline with Chronos2Pipeline.from_pretrained on amazon/chronos-2 as in the README
  5. Read your history into context_df and your future covariate values into future_df
  6. Call pipeline.predict_df with prediction_length, quantile_levels, id_column, timestamp_column and target

These steps come from our top use case, Forecast a series using the drivers you already know, which also has a copy-paste agent prompt.

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Requirements

  • Python with pip and `pip install chronos-forecasting`
  • pandas with pyarrow for the DataFrame examples
  • A CUDA GPU for the README example, which sets device_map to cuda

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Questions about Chronos Forecasting

What is Chronos Forecasting?

Chronos is Amazon Science's family of pretrained time series forecasting models. Chronos-2 forecasts univariate, multivariate and covariate informed tasks zero shot, Chronos-Bolt is a patch based variant the README describes as up to 250 times faster and 20 times more memory efficient than the original Chronos models of the same size, and the original Chronos models tokenize a series and score it with a language model architecture. One pip install gives you the whole family. It is an open-source project on GitHub: https://github.com/amazon-science/chronos-forecasting.

How do I use Chronos Forecasting?

Install it with pip install chronos-forecasting; then load the pipeline with Chronos2Pipeline.from_pretrained on amazon/chronos-2 as in the README; read your history into context_df and your future covariate values into future_df. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is Chronos Forecasting for?

Analysts and engineers who want strong forecasts from a pretrained model instead of fitting one per series.

What can I do with Chronos Forecasting?

3 use cases so far, for example: Forecast a series using the drivers you already know; Chart a forecast with its prediction interval; Choose the Chronos model that fits your budget. Each has steps and a copy-paste agent prompt.

What do I need to run Chronos Forecasting?

Python with pip and `pip install chronos-forecasting`; pandas with pyarrow for the DataFrame examples; A CUDA GPU for the README example, which sets device_map to cuda.

What are alternatives to Chronos Forecasting?

Other hot AI repos in Data and analytics: Crawlee Python, DLT, Timesfm, Ultralytics, Darts.

Is Chronos Forecasting safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.