sentence-bert-base-italian-uncased
nickprock/sentence-bert-base-italian-uncased
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 628
- Total downloadsCumulative all-time download counter reported by the source platform.
- 266.4K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +113(increase)
- 0.0%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 10
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #684 among tracked Sentence Similarity models.
- #39,425
- 462(down 462 places)this week
- Parameters
- 110M
- Last source update
- Mar 14, 2025
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 29.2
- sentence-bert-base-italian-uncased gained 113 downloads during the last seven tracked days.
- It moved from #677 to #684 among tracked Sentence Similarity models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
sentence-bert-base-italian-uncased is a sentence similarity model published by nickprock. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 25h ago.
- Published
- Mar 21, 2023
- Last updated
- Mar 14, 2025
- Library
- sentence-transformers
- License
- mit
- Task
- Sentence Similarity
- Parameters
- 109,928,192
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 16
sentence-transformerspytorchonnxsafetensorsbertfeature-extractionsentence-similaritytransformersitdataset:stsb_multi_mtlicense:mittext-embeddings-inference
Publisher
nickprockView publisher statistics →Similar models
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