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CANDLE
Minimalist ML framework for Rust
Apache-2.0
ABOUT
Python dominates the ML ecosystem but Rust developers who want to integrate ML models directly into Rust applications — CLI tools, edge devices, WebAssembly frontends, or low-latency services — are forced to either call Python subprocesses or use heavyweight bindings. Candle provides native ML primitives in Rust with GPU acceleration and a PyTorch-like API, letting Rust developers run inference on popular models without leaving their language or sacrificing performance.
INSTALL
cargo add candle-coreINTEGRATION GUIDE
1. Run LLM inference in Rust applications without Python dependencies or subprocess overhead
2. Deploy ML models to edge devices and WebAssembly targets using a lightweight Rust-native ML framework
3. Build and fine-tune small transformer models entirely within the Rust ecosystem with GPU acceleration
TAGS
rustmachine-learningdeep-learningframeworkhuggingfacegpuwasminference