BAAI/bge-reranker-base

text-classification model by BAAI

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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…

BAAI/bge-reranker-base on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-09-23T09:30:27.218Z

Inside the original model card — Document outline
  1. News
  2. Model List
  3. Frequently asked questions
  4. Usage
  5. Usage for Embedding Model
  6. Using FlagEmbedding
  7. Using Sentence-Transformers
  8. Using Langchain
  9. Using HuggingFace Transformers
  10. Usage for Reranker
  11. Using FlagEmbedding
  12. 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.

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Model card and usage instructions

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Source: Hugging Face Hub. Metadata observed 2026-09-23T06:37:24.702Z. Daily imports are snapshots, not real-time monitoring.

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