Open standard for machine learning interoperability

Ultralytics YOLOv5 in PyTorch > ONNX > CoreML > TFLite

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages

Lightning-Fast, On-Device, Multilingual TTS — running natively via ONNX.

Ultralytics YOLOv3 in PyTorch > ONNX > CoreML > TFLite

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

Fast ML inference & training for ONNX models in Rust

Lightweight inference library for ONNX files, written in C++. It can run Stable Diffusion XL 1.0 on a RPI Zero 2 (or in 298MB of RAM) but also Mistral 7B on desktops and servers. ARM, x86, WASM, RISC-V supported. Accelerated by XNNPACK. Python, C# and JS(WASM) bindings available.

GPT-SoVITS ONNX Inference Engine & Model Converter

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

Real-time 3D full-body reconstruction from a single camera, Multiperson BVH output, Pure C++ runtime, ONNX + ggml, 70-joint skeleton with hands.