Show HN: Model2vec-Rs – Fast Static Text Embeddings in Rust

Hey HN! We’ve just open-sourced model2vec-rs, a Rust crate for loading and running Model2Vec static embedding models with zero Python dependency. This allows you to embed text at (very) high throughput; for example, in a Rust-based microservice or CLI tool. This can be used for semantic search, retrieval, RAG, or any other text embedding usecase.

Main Features:

- Rust-native inference: Load any Model2Vec model from Hugging Face or your local path with StaticModel::from_pretrained(...).

- Tiny footprint: The crate itself is only ~1.7 mb, with embedding models between 7 and 30 mb.

Performance:

We benchmarked single-threaded on a CPU:

- Python: ~4650 embeddings/sec

- Rust: ~8000 embeddings/sec (~1.7× speedup)

First open-source project in Rust for us, so would be great to get some feedback!

Comments URL: https://news.ycombinator.com/item?id=44021883

Points: 13

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https://github.com/MinishLab/model2vec-rs