ner-roberta-base-ontonotesv5-englishv4
djagatiya/ner-roberta-base-ontonotesv5-englishv4
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 2,833
- Total downloadsCumulative all-time download counter reported by the source platform.
- 24.3K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +274(increase)
- 1.2%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 2
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #760 among tracked Token Classification models.
- #16,321
- 197(down 197 places)this week
- Parameters
- 124M
- Last source update
- May 22, 2024
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 42.8
- ner-roberta-base-ontonotesv5-englishv4 gained 274 downloads during the last seven tracked days.
- It moved from #756 to #760 among tracked Token Classification models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
ner-roberta-base-ontonotesv5-englishv4 is a token classification model published by djagatiya. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it Oct 4, 2026.
- Published
- Jul 1, 2022
- Last updated
- May 22, 2024
- Library
- transformers
- License
- —
- Task
- Token Classification
- Parameters
- 124,084,007
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 39
transformerspytorchsafetensorsrobertatoken-classificationdataset:djagatiya/ner-ontonotes-v5-eng-v4endpoints_compatibleregion:usdeploy:azure
Publisher
djagatiyaView publisher statistics →Similar models
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