ort and rten
These are competitors: both provide ONNX inference engines for Rust, with rten offering simpler lightweight inference while ort provides more comprehensive ML operations including training support.
About ort
pykeio/ort
Fast ML inference & training for ONNX models in Rust
This helps machine learning engineers and MLOps professionals efficiently deploy and run pre-trained machine learning models, regardless of where they were originally built (e.g., PyTorch, TensorFlow). It takes an ONNX-formatted model and data as input, producing fast, hardware-accelerated predictions or training updates. This is ideal for those needing to integrate powerful AI capabilities into applications running on user devices or in data centers.
About rten
robertknight/rten
ONNX neural network inference engine
This project helps developers integrate pre-trained machine learning models, often created in Python frameworks like PyTorch, directly into Rust applications or web-based JavaScript environments. It takes an ONNX model file as input and allows the application to run the model efficiently, producing predictions or classifications. It's designed for developers building applications where machine learning inference needs to run directly within a Rust-powered backend or a web browser.
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