Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
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
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
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
Python package built to ease deep learning on graph, on top of existing DL frameworks.
- deep-learning
- graph-neural-networks
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
- nlp
- embedding
- bert
- ernie
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
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
Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
Translatedcube studio is an open-source, cloud-native, one-stop machine learning / deep learning / large model AI platform. It covers the full mlops algorithm pipeline, a computing power rental platform, online notebook development, drag-and-drop task flow pipeline orchestration, multi-machine multi-GPU distributed training, hyperparameter search, inference services with VGPU virtualization, edge computing, a labeling platform with automated labeling, SFT fine-tuning / reward model / reinforcement learning training for large models such as deepseek, multi-machine large model inference with vllm/ollama/mindie, a private knowledge base, and an AI model marketplace. It supports domestic Chinese CPUs/GPUs/NPUs and the Ascend ecosystem, supports RDMA, and supports distributed frameworks such as pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/ray/volcano.
A unified inference and post-training framework for accelerated video generation.
- diffusers
- diffusion-models
- video-generation
- distillation
MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
Open-source framework for the research and development of foundation models.
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
- tensorflow
- spark
- yahoo
- machine-learning
中文nlp解决方案(大模型、数据、模型、训练、推理)
- bert
- nlp
- transformers
- gpt2
A high-performance distributed training framework for Reinforcement Learning
- reinforcement-learning
- large-scale
- parallelization
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
- deep-learning
- machine-learning
- nvidia-gpu
- physics
Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evolving with slime.