Repository Index

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

• ray
• distributed
• parallel
• machine-learning

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

• deep-learning
• pytorch
• gpu
• machine-learning

Making large AI models cheaper, faster and more accessible

• deep-learning
• hpc
• large-scale
• data-parallelism

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

• python
• deep-learning
• artificial-intelligence
• ai

TranslatedPArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (Core framework of 'PaddlePaddle' (飞桨, Feijiang), for deep learning & machine learning: high-performance single-machine and distributed training, and cross-platform deployment)

• paddlepaddle
• deep-learning
• scalability
• machine-learning

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

• deep-learning
• onnx
• neural-networks
• machine-learning

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

• gbdt
• gbm
• machine-learning
• data-mining

Ongoing research training transformer models at scale

• large-language-models
• model-para
• transformers

Python package built to ease deep learning on graph, on top of existing DL frameworks.

• deep-learning
• graph-neural-networks

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

• ai
• artificial-intelligence
• deep-learning
• large-language-models

Easy-to-use and powerful LLM and SLM library with awesome model zoo.

• nlp
• embedding
• bert
• ernie

PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.

• model

Go ahead and axolotl questions

• fine-tuning
• llm

An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)

• transformers
• vllm
• large-language-models
• raylib

🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

• deep-learning
• machine-learning
• deep-neural-networks
• ml

A unified ecosystem and workspace for large-scale federated learning of Large Models & LLMS. Store compute as Wifi

• compute-orchestration
• distributed-systems
• edge-computing
• edge-intelligence

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

Flower: A Friendly Federated AI Framework

• flower
• federated-learning
• federated-learning-framework
• federated-analytics

A Flexible and Powerful Parameter Server for large-scale machine learning

• machine-learning
• parameter-server
• spark
• scala

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

• tensorflow
• deep-learning
• reinforcement-learning
• neural-networks

A unified ecosystem and workspace for large-scale federated learning, bridging the gap between centralized model evolution and decentralized edge intelligence.

Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL

Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark

• spark
• pyspark
• azure
• scala