maple-preview
deepgrove/maple-preview
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 7,069
- Total downloadsCumulative all-time download counter reported by the source platform.
- 7,069
- 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.
- 375
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #2507 among tracked Text Generation models.
- #9,472
- 7828(down 7828 places)this week
- Parameters
- 20.2B
- Last source update
- Aug 4, 2026
- It moved from #526 to #2507 among tracked Text Generation models this week.
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
maple-preview is a text generation model published by deepgrove. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 13 min ago.
- Published
- Aug 4, 2026
- Last updated
- Aug 4, 2026
- Library
- transformers
- License
- mit
- Task
- Text Generation
- Parameters
- 20,214,030,336
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
transformerssafetensorstext-generationcausal-lmmixture-of-expertsreasoningternarycustom-codeconversationalcustom_codeenlicense:mit
Publisher
deepgroveView publisher statistics →Similar models
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