How to template AI software in Red Hat Developer Hub
Learn how to use Red Hat Developer Hub to easily create and deploy applications to your image repository or a platform like Red Hat OpenShift AI.
Learn how to use Red Hat Developer Hub to easily create and deploy applications to your image repository or a platform like Red Hat OpenShift AI.
Use AI and Node.js to generate a JSON response that contains a summarized email
Learn how to safely deploy and operate AI services without compromising on...
A practical example to deploy machine learning model using data science...
Learn how to set up a cloud development environment (CDE) using Ollama, Continue
Podman Desktop provides a graphical interface for application developers to work seamlessly with containers and Kubernetes in a local environment.
In this course, you’ll explore how to configure your RHEL AI machine, download
Artificial intelligence (AI) and large language models (LLMs) are becoming
The rapid advancement of generative artificial intelligence (gen AI) has unlocked incredible opportunities. However, customizing and iterating on large language models (LLMs) remains a complex and resource intensive process. Training and enhancing models often involves creating multiple forks, which can lead to fragmentation and hinder collaboration.
OCI images are now available on the registries Docker Hub and Quay.io, making it even easier to use the Granite 7B large language model (LLM) and InstructLab.
Announcing the General Availability of Red Hat Enterprise Linux AI (RHEL AI)
Get started with AMD GPUs for model serving in OpenShift AI. This tutorial guides you through the steps to configure the AMD Instinct MI300X GPU with KServe.
Learn how developers can use prompt engineering for a large language model (LLM) to increase their productivity.
Learn how to deploy a coding copilot model using OpenShift AI. You'll also discover how tools like KServe and Caikit simplify machine learning model management.
This tutorial gives you a unique chance to learn, hands-on, some of the basics of large language models (LLMs) in the Developer Sandbox for Red Hat OpenShift.
Explore AMD Instinct MI300X accelerators and learn how to run AI/ML workloads using ROCm, AMD’s open source software stack for GPU programming, on OpenShift AI.
Learn how to apply supervised fine-tuning to Llama 3.1 models using Ray on OpenShift AI in this step-by-step guide.
Understand how retrieval-augmented generation (RAG) works and how users can
Experimenting with a Large Language Model powered Chatbot with Node.js
Learn how to rapidly prototype AI applications from your local environment with
Learn how to generate word embeddings and perform RAG tasks using a Sentence Transformer model deployed on Caikit Standalone Serving Runtime using OpenShift AI.
In today's fast-paced IT landscape, the need for efficient and effective
Add knowledge to large language models with InstructLab and streamline MLOps using KitOps for efficient model improvement and deployment.
Learn how a platform engineering team streamlined the deployment of edge kiosks by leveraging key automation components of Red Hat Ansible Automation Platform.
With GPU acceleration for Podman AI Lab, developers can inference models faster and build AI-enabled applications with quicker response times.