Stars
Efficient Triton Kernels for LLM Training
Distributed ML Training and Fine-Tuning on Kubernetes
DeepGNN is a framework for training machine learning models on large scale graph data.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
🦜🔗 Build context-aware reasoning applications
Caikit is an AI toolkit that enables users to manage models through a set of developer friendly APIs.
Interpretability and explainability of data and machine learning models
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Source code for Twitter's Recommendation Algorithm
A conda-smithy repository for kfp-tekton.
Curated list of awesome tools for managing open source programs
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A toolkit to run Ray applications on Kubernetes
Elyra extends JupyterLab with an AI centric approach.
A multi-cloud framework for big data analytics and embarrassingly parallel jobs, that provides an universal API for building parallel applications in the cloud ☁️🚀
Bootstrap Kubernetes the hard way. No scripts.
Machine Learning eXchange (MLX). Data and AI Assets Catalog and Execution Engine
Official electron build of draw.io
A kubernetes based framework for hassle free handling of datasets
Experimental project plugging Tekton yaml behind KFP API and UI engine
A repository to host extended examples and tutorials