chronos-t5-large
amazon/chronos-t5-large
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 129.8K
- Total downloadsCumulative all-time download counter reported by the source platform.
- 10.9M
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- —
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 179
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #29 among tracked Time Series Forecasting models.
- #2,168
- –this week
- Parameters
- 709M
- Last source update
- Nov 21, 2025
Downloads over time
Cumulative total downloads observed by OpenModelStatsNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Likes over time
Not enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Rank among tracked models
Lower is betterNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Overview
chronos-t5-large is a time series forecasting model published by amazon. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 1h ago.
- Published
- Feb 21, 2024
- Last updated
- Nov 21, 2025
- Library
- chronos-forecasting
- License
- apache-2.0
- Task
- Time Series Forecasting
- Parameters
- 708,963,328
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
chronos-forecastingsafetensorst5time seriesforecastingpretrained modelsfoundation modelstime series foundation modelstime-seriestime-series-forecastingarxiv:2403.07815arxiv:1910.10683
Publisher
amazonView publisher statistics →Similar models
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