OpenMed-NER-GenomeDetect-PubMed-109M
OpenMed/OpenMed-NER-GenomeDetect-PubMed-109M
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 118.4K
- Total downloadsCumulative all-time download counter reported by the source platform.
- 1.4M
- 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. #73 among tracked Token Classification models.
- #2,245
- –this week
- Parameters
- 109M
- Last source update
- Aug 5, 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
OpenMed-NER-GenomeDetect-PubMed-109M is a token classification model published by OpenMed. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 3h ago.
- Published
- Jul 16, 2025
- Last updated
- Aug 5, 2025
- Library
- transformers
- License
- apache-2.0
- Task
- Token Classification
- Parameters
- 108,893,955
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
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transformerssafetensorsberttoken-classificationnamed-entity-recognitionbiomedical-nlpgene-recognitionprotein-recognitiongenomicsmolecular-biologygene/proteinen
Publisher
OpenMedView publisher statistics →Similar models
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