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bge-reranker-v2-m3
beclab/bge-reranker-v2-m3
bge-reranker-v2-m3 is a machine learning model from beclab. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Unified Hugging Face release for RerankServer / llm-init.
Access
Public
Updated Sep 5, 2026
Repo size
4.6 GB
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Repo makeup
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.bin2.3 GB · 50%
At a glance
- Access
- Public
- Created
- Sep 5, 2026
- Updated
- Sep 5, 2026
- SHA
- d7af0d01
Model card
From the Hugging Face model README
BGE-Reranker-v2-m3（OpenVINO + ONNX）
Unified Hugging Face release for RerankServer / llm-init.
Layout matches beclab/embeddinggemma-300m: one logical model, two complete format trees. FP16 exports are not included.
| Subdirectory | Format | Runtime | Key files |
|---|---|---|---|
| openvino/ | OpenVINO IR FP32 | RERANK_RUNTIME=openvino (ACCELERATOR=intel-gpu) | openvino_model.xml, openvino_model.bin |
| onnx/ | ONNX FP32 | RERANK_RUNTIME=onnx (cpu / nvidia / nvidia-gb10) | model.onnx, model.onnx_data |
Logical model name (MODEL_ID / OpenAI model): bge-reranker-v2-m3.
RerankServer
MODEL_DIR must point at the format subdirectory (openvino/ or onnx/), not this repo root.
Tokenizer lives in the same subdirectory (tokenizer.json).
llm-init
MODEL_SOURCE=hf://beclab/bge-reranker-v2-m3
MODEL_NAME=bge-reranker-v2-m3
MODEL_MODE=rerank
License
Same as BAAI/bge-reranker-v2-m3.
- Created
- Sep 5, 2026
- Updated
- Sep 5, 2026