From the model card
Fields below are copied from the tags and counters on the HuggingFace repository autogluon/chronos-bolt-small 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)
- autogluon
- 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)
- 6,146,037
- Likes (HF counter at last fetch)
- 61
- Model card
- https://huggingface.co/autogluon/chronos-bolt-small
Use cases
- Rapid zero-shot forecasting for new datasets without training
- Time-series exploration and baseline evaluation
- Resource-constrained deployment where Chronos-2 is too large
- Batch forecasting across many series where latency matters
- AutoGluon pipeline integration for automated time-series modeling
Pros
- Small model size enables faster inference than full Chronos-2
- Zero-shot forecasting without per-dataset training
- Apache 2.0 license
- AutoGluon ecosystem integration for end-to-end ML pipelines
Cons
- Bolt-small trades accuracy for speed vs. Bolt-base or Chronos-2
- Token-based quantization adds discretization error vs. continuous methods
- Performance varies significantly by domain and time-series type
- Requires AutoGluon or custom T5 code for inference — no transformers.pipeline wrapper
- Not competitive with statistical methods (ETS, ARIMA) on short, regular series
Tags
safetensorst5time seriesforecastingpretrained modelsfoundation modelstime series foundation modelstime-seriestime-series-forecastingarxiv:1910.10683arxiv:2403.07815license:apache-2.0region:us