Download
rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. The library integrates with Rust machine learning infrastructure using crates such as tch-rs and ONNX Runtime for model execution. It also includes tokenization utilities, model architectures, and task-specific pipelines that simplify the development of NLP applications. Because Rust is known for its safety and performance, this project enables developers to deploy modern NLP models in production systems written in Rust.
Features
- Rust implementation of transformer-based NLP models
- Support for models such as BERT, DistilBERT, and GPT-2
- Ready-to-use pipelines for common NLP tasks
- Integration with tch-rs and ONNX Runtime for model execution
- Multithreaded tokenization for high-performance preprocessing
- Production-friendly deployment in Rust applications
Project Samples
