Results for coreml_predict

pure Rust driver for Apple Neural Engine

Safe Rust bindings for Apple CoreML — models, features, updates, compute plans, and stateful inference on macOS

Safe, ergonomic Rust bindings for Apple CoreML inference with ANE acceleration

W3C WebNN implementation with ONNX, CoreML, and TensorRT backends [DO NOT USE IN PRODUCTION - Development Release]

Ultralytics YOLO inference library and CLI for Rust

CoreML inference engine for Candle tensors - provides Apple CoreML/ANE integration with real tokenization, safety fixes, and model calibration awareness

Apple CoreML execution provider for OxiONNX — load and run pre-converted .mlpackage models on ANE / GPU / CPU

Object detection using ORT and the yoloe-26-seg model. This model can detect multiple objects per image, each having a tag, pixel-level mask, and a boundingbox. It's pretrained, it has a vocabulary of 4000+ objects.

A native Rust CLI for Kokoro TTS using XDG standards and agent-first design

CoreML bindings for Rust using swift-bridge to maximize performance

High-performance ONNX recognition pipeline for Chinese chessboard corners and pieces.

Production-ready PyTorch-compatible deep learning library in Rust with special mathematical functions (gamma, Bessel, error functions), statistical distributions, Fourier transforms (FFT/RFFT), matrix decomposition (SVD/QR/LU/eigenvalue), automatic differentiation, neural networks, computer vision transforms, complete GPU acceleration (CUDA/Metal/OpenCL), SIMD optimizations, parallel processing, WebAssembly browser support, comprehensive distributed learning support, and performance validation