bge-reranker-v2-m3
BAAI/bge-reranker-v2-m3
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 18.6M
- Total downloadsCumulative all-time download counter reported by the source platform.
- 123.7M
- 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.
- 1,142
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #1 among tracked Text Classification models.
- #16
- 4(down 4 places)this week
- Parameters
- 568M
- Last source update
- Jun 24, 2024
Downloads over time
Daily gain between consecutive observationsNot 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
bge-reranker-v2-m3 is a text classification model published by BAAI. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 41 min ago.
- Published
- Mar 15, 2024
- Last updated
- Jun 24, 2024
- Library
- sentence-transformers
- License
- apache-2.0
- Task
- Text Classification
- Parameters
- 567,755,777
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
sentence-transformerssafetensorsxlm-robertatext-classificationtransformerstext-embeddings-inferencemultilingualarxiv:2312.15503arxiv:2402.03216license:apache-2.0endpoints_compatibleregion:us
Publisher
BAAIView publisher statistics →Similar models
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