Popular GitHub Repositories for Distributed Ml

An Open Source Machine Learning Framework for Everyone

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

YOLOv5 ? in PyTorch > ONNX > CoreML > TFLite

100 Days of ML Coding

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Making large AI models cheaper, faster and more accessible

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

Visualizer for neural network, deep learning and machine learning models

Cross-platform, customizable ML solutions for live and streaming media.

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

? A ranked list of awesome machine learning Python libraries. Updated weekly.

Open source platform for the machine learning lifecycle

Universal LLM Deployment Engine with ML Compilation

? The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Open standard for machine learning interoperability

A WebGL accelerated JavaScript library for training and deploying ML models.