Taxonomy tree that will allow you to create models tuned with your data

Python library for Synthetic Data Generation

Artifacts for installing the Distributed Workloads stack as part of ODH

The goal of RamaLama is to make working with AI boring.

InstructLab Training Library

Examples for building and running LLM services and applications locally with Podman

Python bindings for llama.cpp

Port of Facebook's LLaMA model in C/C++

Source for "Streamlining insurance claims with OpenShift AI" Lab

A cloud-native vector database, storage for next generation AI applications

Machine Learning Engineering Open Book

🤖 The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs ggml, gguf, GPTQ,…

A self-hosted, offline, ChatGPT-like chatbot. Powered by Llama 2. 100% private, with no data leaving your device. New: Code Llama support!

Improve ROSA customer experience (and customer retention) by leveraging foundation models to do “gpt-chat” style search of Red Hat customer documentation assets.

An intuitive, easy-to-use python interface for batch resource requesting, access, job submission, and observation. Simplifying the developer's life while enabling access to high-performance compute…

SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.

A question-answering system that uses embeddings and a language model to find the most likely answer to a question, while also providing links to sources that support the answer.

LlamaIndex (GPT Index) is a data framework for your LLM applications

Caikit is an AI toolkit that enables users to manage models through a set of developer friendly APIs.

Large Language Model Text Generation Inference

Inference code for LLaMA models

TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.

A toolkit to run Ray applications on Kubernetes

On-demand Kubernetes/OpenShift cluster scaling and aggregated resource provisioning

Code and documentation to train Stanford's Alpaca models, and generate the data.