Popular GitHub Repositories for Ios Coreml

? Light and Fast AI Assistant. Support: Web | iOS | MacOS | Android | Linux | Windows

YOLOv5 ? in PyTorch > ONNX > CoreML > TFLite

Visualizer for neural network, deep learning and machine learning models

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Filament是一个实时物理渲染引擎，支持Android、iOS、Windows、Linux、macOS和WebGL2平台。

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

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

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Run Stable Diffusion on Mac natively

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, support 11 programming languages

Collection of models for Core ML

Firebase SDK for Apple App Development

Flower: A Friendly Federated AI Framework

The Swift machine learning library.

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

Enchanted is iOS and macOS app for chatting with private self hosted language models such as Llama2, Mistral or Vicuna using Ollama.

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

On-device Speech Recognition for Apple Silicon

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.