BAAI/bge-reranker-v2-m3
text-classification model by BAAI
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
More details please refer to our Github: FlagEmbedding. Different from embedding model, reranker uses question and document as input and directly output similarity instead of embedding. You can get a relevance score by inputting query and passage to the reranker. And the score can be mapped to a float value in [0,1] by sigmoid function. You can select the model according your senario and resource. Get relevance scores (higher scores indicate more relevance): Get relevance scores (higher scores indicate more relevance): Train data should be a json file, where each line is a dict like this: query is the query, and pos is a list of positive texts, neg is a list of negative texts, prompt indicates the relationship between query and texts. If you have no negative texts for a query, you can random sample some from the entire corpus as the negatives.…
Read the full model card ↗ · Preview checked 2026-10-28T00:28:53.162Z
Inside the original model card — Document outline
- Reranker
- Model List
- Usage
- Using FlagEmbedding
- For normal reranker (bge-reranker-base / bge-reranker-large / bge-reranker-v2-m3 )
- For LLM-based reranker
- For LLM-based layerwise reranker
- Using Huggingface transformers
- For normal reranker (bge-reranker-base / bge-reranker-large / bge-reranker-v2-m3 )
- For LLM-based reranker
- For LLM-based layerwise reranker
- Fine-tune
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
BAAI/bge-reranker-v2-m3 is a text-classification model repository published by BAAI on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-classification
- Library
- sentence-transformers
- Recent downloads (30 days)
- 14,677,242
- Cumulative likes
- 1,284
- Hugging Face trending score
- 5
- Reported safetensors parameters
- 567,755,777
- Architecture
- XLMRobertaForSequenceClassification
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2024-03-15T13:32:18.000Z
- Last modified
- 2024-06-24T14:08:45.000Z
Compatibility and lineage
Reported languages: multilingual
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:49:31.990Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.