bge-reranker-base

Lighter reranker for Dakera · a verified mirror by Dakera, the self-hosted memory engine for AI agents

An unmodified, checksum-verified copy of the files Dakera uses from BAAI/bge-reranker-base. The model is by BAAI; all credit goes to its authors.

In Dakera

A smaller English cross-encoder reranker: DAKERA_RERANKER_MODEL=bge-reranker-base.

Dakera fetches this reranker from this repository first and from the original repositories if it is unreachable, so installs never depend on a single source. Both are checked against the same SHA-256, and the Dakera Docker image ships the default models ready to run, with no download at startup.

Files

Copied byte for byte from:

File	Source	Size
onnx/model_int8.onnx	Xenova/bge-reranker-base	278.8 MB
tokenizer.json	Xenova/bge-reranker-base	17.1 MB

SHA-256 checksums

2059d8ef0b6e935b4845e11b38c9af9e9e2e7b91f69fc99efe03254e0a7da8d3  onnx/model_int8.onnx
48564c5c7d3fa64d85d95e65414a542385f88b0f128fd8d4163fd7a57f2be05c  tokenizer.json

Licence and credit

MIT, the same as the original model (see LICENSE). For what the model does, how it was trained and how to cite it, see the original model card.

About Dakera

Dakera is a self-hosted memory engine for AI agents. It gives agents long-term memory that survives sessions: hybrid vector and full-text retrieval, reranking, entity extraction and importance decay, in a single Rust binary that runs on your own servers, with an MCP server for Claude, Cursor and other agents.

docker run -p 3000:3000 -e DAKERA_ROOT_API_KEY=dk-mykey ghcr.io/dakera-ai/dakera:latest

🌐 Website	dakera.ai
📚 Documentation	dakera.ai/docs
💻 GitHub	github.com/Dakera-AI
🚀 Self-hosting (Docker, Kubernetes, Helm)	dakera-deploy
🔌 MCP server	dakera-mcp
🧰 SDKs	Python · TypeScript · Go · Rust
💼 LinkedIn	Dakera AI

Questions or feedback: amine@dakera.ai.