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time series forecasting by amazon

chronos-bolt-base

Chronos-Bolt-Base is the base-size variant of Amazon's improved Chronos forecasting model series, using a T5 encoder-decoder architecture. The Bolt series improves training efficiency over the original Chronos through revised architectural choices, achieving better forecast accuracy at equivalent model sizes. Apache 2.0 licensed.

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From the model card

Fields below are copied from the tags and counters on the HuggingFace repository amazon/chronos-bolt-base at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.

Publisher (HF namespace)
amazon
Pipeline tag
time-series-forecasting
Weight formats
safetensors
License tag
apache-2.0 — read the license file in the repo before relying on it
Papers cited
arXiv:1910.10683, arXiv:2403.07815
Downloads (HF counter at last fetch)
1,166,830
Likes (HF counter at last fetch)
92
Model card
https://huggingface.co/amazon/chronos-bolt-base

Use cases

  • Zero-shot time-series forecasting across diverse domains
  • Forecasting pipeline benchmarks against traditional statistical methods
  • Demand planning prototyping without per-dataset training
  • Multi-horizon forecasting with variable horizon lengths
  • Ensemble component in combined forecasting systems

Pros

  • Improved accuracy over original Chronos at equivalent size via Bolt training
  • Apache 2.0 license
  • Zero-shot domain transfer without fine-tuning
  • T5 architecture handles variable forecast horizons

Cons

  • Requires custom chronos-forecasting library code or AutoGluon for inference
  • Not competitive with dataset-specific models on narrow single-domain tasks
  • Token quantization introduces discretization error for continuous series
  • Higher latency than classical statistical forecasting methods
  • Performance on irregular or event-driven series is limited

Tags

chronos-forecastingsafetensorst5time seriesforecastingpretrained modelsfoundation modelstime series foundation modelstime-seriestime-series-forecastingarxiv:1910.10683arxiv:2403.07815license:apache-2.0region:usdeploy:sagemaker