Chronos T5 Mini is a pretrained time series foundation model hosted on Hugging Face. Developed by Amazon, it belongs to the class of time series forecasting foundation models and is based on the T5 architecture.
The model generates probabilistic forecasts from historical time series data. It accepts context data via a pandas dataframe, produces multi-step predictions, and returns specified quantiles such as 0.1, 0.5, and 0.9. A simple pipeline interface handles loading the model, preparing input, and generating output in a few lines of code.
It is delivered as a model repository on the Hugging Face platform. Users install the companion chronos-forecasting Python package and instantiate BaseChronosPipeline.from_pretrained with the identifier amazon/chronos-t5-mini. The pipeline supports device mapping including CUDA for accelerated inference. Example usage loads a CSV file containing passenger data and forecasts 36 steps ahead while estimating the requested quantiles.
The model card lists it under the Apache-2.0 license. It is accompanied by references to two arXiv papers that describe the underlying methods. The repository provides safetensors weights and is tagged for time-series, foundation-models, and pretrained use.
Chronos T5 Mini sits in PulseGate's Data science & ML workbench category. It focuses on forecasting future values in time series data without requiring task-specific training. Chronos T5 Mini is an open-source project aimed at data scientists. The project is open source (Apache-2.0). Chronos T5 Mini is available on the web, the command line, and API.
Amazon builds and maintains Chronos T5 Mini, and the product first shipped in 2024. The project is developed in the open on GitHub with 5.6k stars and 10 commits in the last 90 days. Among its 4 catalogued features are Time Series Forecasting, Probabilistic Predictions, and Quantile Forecasting.
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