Recurrent-OLMo-2-0425-train-recurrence-16
smcleish/Recurrent-OLMo-2-0425-train-recurrence-16
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 8,930
- Total downloadsCumulative all-time download counter reported by the source platform.
- 9,065
- 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.
- 0
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #2020 among tracked Text Generation models.
- #8,241
- –this week
- Parameters
- 1.4B
- Last source update
- Nov 11, 2025
Downloads over time
Daily gain between consecutive observationsNot 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
Recurrent-OLMo-2-0425-train-recurrence-16 is a text generation model published by smcleish. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 2h ago.
- Published
- Nov 8, 2025
- Last updated
- Nov 11, 2025
- Library
- transformers
- License
- apache-2.0
- Task
- Text Generation
- Parameters
- 1,359,071,232
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
transformerssafetensorshuginn_raventext-generationcausal-lmcustom_codeendataset:nvidia/Nemotron-CC-Math-v1arxiv:2511.07384license:apache-2.0region:us
Publisher
smcleishView publisher statistics →Similar models
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