all-mpnet-base-v2-negation
dmlls/all-mpnet-base-v2-negation
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 312
- Total downloadsCumulative all-time download counter reported by the source platform.
- 37.4K
- 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.
- 2
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #801 among tracked Sentence Similarity models.
- #29,746
- –this week
- Parameters
- 109M
- Last source update
- Oct 28, 2024
Downloads over time
Rolling recent-window downloads as reportedNot 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
all-mpnet-base-v2-negation is a sentence similarity model published by dmlls. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 2h ago.
- Published
- Apr 7, 2023
- Last updated
- Oct 28, 2024
- Library
- sentence-transformers
- License
- apache-2.0
- Task
- Sentence Similarity
- Parameters
- 109,486,978
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
sentence-transformerspytorchsafetensorsmpnetfeature-extractionsentence-similarityendataset:s2orcdataset:flax-sentence-embeddings/stackexchange_xmldataset:ms_marcodataset:gooaqdataset:yahoo_answers_topics
Publisher
dmllsView publisher statistics →Similar models
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