Awesome Opensource Ai

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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

The fastai deep learning library

Open3D: A Modern Library for 3D Data Processing

Open Machine Learning Compiler Framework

NumPy & SciPy for GPU

The Triton Inference Server provides an optimized cloud and edge inferencing solution.

Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem).

cuDF - GPU DataFrame Library

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.

FlashInfer: Kernel Library for LLM Serving

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

cuML - RAPIDS Machine Learning Library

Time series forecasting with PyTorch

On-device AI across mobile, embedded and edge for PyTorch

Achieve state of the art inference performance with modern accelerators on Kubernetes

cuGraph - RAPIDS Graph Analytics Library

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.