bge-reranker-base
We have updated the new reranker, supporting larger lengths, more languages, and achieving better performance.
Params
280 M
Context
512
Downloads 30d
2.4 M
Likes
263
Download history
daily snapshots · 106 days
▲ 1.6 M in the last 30 days (40.1%)
3.9 M2.4 M
Oct 12Oct 22Nov 1Nov 10
4.2 M2.4 M
Aug 13Sep 12Oct 12Nov 10
4.9 M2.4 M
Jul 28Sep 1Oct 6Nov 10
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 1.1 GB | 1.8 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- XLMRobertaForSequenceClassification
- Parameters
- 280 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 250,002
- Layers / heads
- 12 / 12
- Licence
- mit
- First seen on the Hub
- 2023-09-11
- Training datasets
- undisclosed
- MTEB CMedQAv1 (reported)
- 84.142380952381
- MTEB CMedQAv2 (reported)
- 86.79376984127
- MTEB T2Reranking (reported)
- 77.131519274376
- MTEB MMarcoReranking (reported)
- 34.602380952381
- Added to our catalog
- 2026-07-28
Compare with any text-classification model