Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes

Enable RHOAI User Workload Metrics for Single Serving Models

Tools and technologies that are hosted on an OpenShift cluster

Notes for offline OCP + RHOAI install

Artifacts for the Distributed Workloads stack as part of ODH

Evaluate and Enhance Your LLM Deployments for Real-World Inference Needs

A high-throughput and memory-efficient inference and serving engine for LLMs

OpenWebUI + LiteLLM + SemanticRouter + vLLM -> LLM semantic routing demo with Lora

The AI Accelerator is a template project for setting up Red Hat OpenShift AI using GitOps

Example repository used for demo purposes - contains Ansible playbooks and uses a requirements.yml to pull Ansible Roles

Machine Learning Pipelines for Kubeflow

This repo contains the code and data needed by the instructor to deploy the lab.

This repo contains the charts needed for the student to deploy lab components

This repo contains the scenario notebooks and pipelines.

This repo contains the follow-along student instructions for the lab. https://rhoai-mlops.github.io/lab-instructions/

AI-on-OpenShift website source code

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Declarative continuous deployment for Kubernetes.

Spark operator deployment and usage on OpenShift