BAAI/bge-reranker-base
text-classification model by BAAI
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Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
We have updated the new reranker, supporting larger lengths, more languages, and achieving better performance. FlagEmbedding More details please refer to our Github: FlagEmbedding. English | 中文 FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: It is the first embedding model which supports all three retrieval methods, achieving new SOTA on multi-lingual (MIRACL) and cross-lingual (MKQA) benchmarks. Technical Report and Code. :fire: More bge is short for BAAI general embedding. For examples, use bge embedding model to retrieve top 100 relevant documents, and then use bge reranker to re-rank the top 100 document to get the final top-3 results. All models have been uploaded to Huggingface Hub, and you can see them at https://huggingface.co/BAAI. If you cannot open the Huggingface Hub, you also can download the models at https://model.baai.ac.cn/models . Following this example to prepare data and fine-tune your model. Some suggestions: Hard negatives also are needed…
Read the full model card ↗ · Preview checked 2026-09-23T09:30:27.218Z
Inside the original model card — Document outline
- News
- Model List
- Frequently asked questions
- Usage
- Usage for Embedding Model
- Using FlagEmbedding
- Using Sentence-Transformers
- Using Langchain
- Using HuggingFace Transformers
- Usage for Reranker
- Using FlagEmbedding
- Using Huggingface transformers
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Documentation belongs to its respective authors. Reported project/model license: mit. 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-base 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)
- 4,172,439
- Cumulative likes
- 247
- Hugging Face trending score
- 1
- Reported safetensors parameters
- 278,044,931
- Architecture
- XLMRobertaForSequenceClassification
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2023-09-11T12:30:04.000Z
- Last modified
- 2024-06-24T14:10:03.000Z
Compatibility and lineage
Reported languages: en, zh
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 2026-09-23T06:37:24.702Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.