model2vec-rs

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!