#72 · Primary category： Knowledge Base & RAG
fastembed
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Project last updated：08/26/26
GitHub Stars
3.2K
Forks
239
Contributors
31
License
Apache-2.0
Why we included this project
FastEmbed keeps the embedding step light by running compact models on ONNX Runtime, so you can turn text into vectors without a GPU or a full PyTorch install. That makes it a comfortable fit for serverless runtimes and small services where dependency weight matters. The default TextEmbedding model is Flag Embedding, which uses separate query and passage prefixes, and the API stays simple: documents in, a generator of vectors out. If you are wiring up retrieval or vector search and want embeddings that come fast without dragging in heavy machinery, this is a practical starting point.
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