OpenMed-ZeroShot-NER-Oncology-Small-166M
OpenMed/OpenMed-ZeroShot-NER-Oncology-Small-166M
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 25.6K
- Total downloadsCumulative all-time download counter reported by the source platform.
- 169K
- 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.
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- LikesCommunity likes reported by the source platform.
- 0
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #436 among tracked Token Classification models.
- #5,040
- –this week
- Parameters
- —
- Last source update
- Oct 19, 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-ZeroShot-NER-Oncology-Small-166M is a token classification model published by OpenMed. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 3h ago.
- Published
- Sep 15, 2025
- Last updated
- Oct 19, 2025
- Library
- gliner
- License
- apache-2.0
- Task
- Token Classification
- Parameters
- —
- Spaces
- —
- Derivative models
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- Velocity 7D/day
- —
glinerpytorchtoken-classificationentity recognitionnamed-entity-recognitionzero-shotzero-shot-nerzero shotbiomedical-nlpcancer-geneticsoncologygene-regulation
Publisher
OpenMedView publisher statistics →Similar models
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