bert-base-multilingual-uncased-sentiment
nlptown/bert-base-multilingual-uncased-sentiment
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 896.2K
- Total downloadsCumulative all-time download counter reported by the source platform.
- 66.9M
- 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.
- 481
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #13 among tracked Text Classification models.
- #492
- 229(down 229 places)this week
- Parameters
- 167M
- Last source update
- Jan 2, 2025
- It moved from #7 to #13 among tracked Text Classification 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
bert-base-multilingual-uncased-sentiment is a text classification model published by nlptown. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 6h ago.
- Published
- Mar 2, 2022
- Last updated
- Jan 2, 2025
- Library
- transformers
- License
- mit
- Task
- Text Classification
- Parameters
- 167,360,261
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
transformerspytorchtfjaxsafetensorsberttext-classificationennldefrit
Publisher
nlptownView publisher statistics →Similar models
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